Supertonic 2

Fix iOS TTS call signature and streamline demo code

README.md

@@ -1,33 +1,53 @@
 # Supertonic — Lightning Fast, On-Device TTS
 
-[![Demo](https://img.shields.io/badge/🤗%20Hugging%20Face-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo)
+[![v2 Demo](https://img.shields.io/badge/🤗%20v2-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic-2)
-[![Models](https://img.shields.io/badge/🤗%20Hugging%20Face-Models-blue)](https://huggingface.co/Supertone/supertonic)
+[![v2 Models](https://img.shields.io/badge/🤗%20v2-Models-blue)](https://huggingface.co/Supertone/supertonic-2)
+[![v1 Demo](https://img.shields.io/badge/🤗%20v1%20(old)-Demo-lightgrey)](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo)
+[![v1 Models](https://img.shields.io/badge/🤗%20v1%20(old)-Models-lightgrey)](https://huggingface.co/Supertone/supertonic)
 
 <p align="center">
-  <img src="img/Supertonic_IMG_v02_4x.webp" alt="Supertonic Banner">
+  <img src="img/supertonic_preview_0.1.jpg" alt="Supertonic Banner">
 </p>
 
 **Supertonic** is a lightning-fast, on-device text-to-speech system designed for **extreme performance** with minimal computational overhead. Powered by ONNX Runtime, it runs entirely on your device—no cloud, no API calls, no privacy concerns.
 
-Watch Supertonic running on a **Raspberry Pi**—demonstrating on-device, real-time text-to-speech synthesis:
+### 📰 Update News
 
-https://github.com/user-attachments/assets/ea66f6d6-7bc5-4308-8a88-1ce3e07400d2
+- **2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
-
+- **2025.12.10** - Added `supertonic` PyPI package! Install via `pip install supertonic`. For details, visit [supertonic-py documentation](https://supertone-inc.github.io/supertonic-py)
-> 🎧 **Try it now**: Experience Supertonic in your browser with our [**Interactive Demo**](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo), or get started with pre-trained models from [**Hugging Face Hub**](https://huggingface.co/Supertone/supertonic)
+- **2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
-
+- **2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
-## 📰 Update News
+- **2025.11.24** - Added Flutter SDK support with macOS compatibility
-
-**2025.11.24** - Added Flutter SDK support with macOS compatibility
 
 ### Table of Contents
 
+- [Demo](#demo)
 - [Why Supertonic?](#why-supertonic)
 - [Language Support](#language-support)
 - [Getting Started](#getting-started)
 - [Performance](#performance)
+- [Built with Supertonic](#built-with-supertonic)
 - [Citation](#citation)
 - [License](#license)
 
+## Demo
+
+### Raspberry Pi
+
+Watch Supertonic running on a **Raspberry Pi**, demonstrating on-device, real-time text-to-speech synthesis:
+
+https://github.com/user-attachments/assets/ea66f6d6-7bc5-4308-8a88-1ce3e07400d2
+
+### E-Reader
+
+Experience Supertonic on an **Onyx Boox Go 6** e-reader in airplane mode, achieving an average RTF of 0.3× with zero network dependency:
+
+https://github.com/user-attachments/assets/64980e58-ad91-423a-9623-78c2ffc13680
+
+---
+
+> 🎧 **Try it now**: Experience Supertonic in your browser with our [**Interactive Demo**](https://huggingface.co/spaces/Supertone/supertonic-2), or get started with pre-trained models from [**Hugging Face Hub**](https://huggingface.co/Supertone/supertonic-2)
+
 ## Why Supertonic?
 
 - **⚡ Blazingly Fast**: Generates speech up to **167× faster than real-time** on consumer hardware (M4 Pro)—unmatched by any other TTS system
@@ -75,7 +95,7 @@ Before running the examples, download the ONNX models and preset voices, and pla
 > - Generic: see `https://git-lfs.com` for installers
 
 ```bash
-git clone https://huggingface.co/Supertone/supertonic assets
+git clone https://huggingface.co/Supertone/supertonic-2 assets
 ```
 
 ### Quick Start
@@ -235,12 +255,12 @@ Supertonic is designed to handle complex, real-world text inputs that contain nu
 
 **Overview of Test Cases:**
 
-| Category | Key Challenges | Supertonic | ElevenLabs | OpenAI | Gemini |
+| Category | Key Challenges | Supertonic | ElevenLabs | OpenAI | Gemini | Microsoft |
-|:--------:|:--------------:|:----------:|:----------:|:------:|:------:|
+|:--------:|:--------------:|:----------:|:----------:|:------:|:------:|:---------:|
-| Financial Expression | Decimal currency, abbreviated magnitudes (M, K), currency symbols, currency codes | ✅ | ❌ | ❌ | ❌ |
+| Financial Expression | Decimal currency, abbreviated magnitudes (M, K), currency symbols, currency codes | ✅ | ❌ | ❌ | ❌ | ❌ |
-| Time and Date | Time notation, abbreviated weekdays/months, date formats | ✅ | ❌ | ❌ | ❌ |
+| Time and Date | Time notation, abbreviated weekdays/months, date formats | ✅ | ❌ | ❌ | ❌ | ❌ |
-| Phone Number | Area codes, hyphens, extensions (ext.) | ✅ | ❌ | ❌ | ❌ |
+| Phone Number | Area codes, hyphens, extensions (ext.) | ✅ | ❌ | ❌ | ❌ | ❌ |
-| Technical Unit | Decimal numbers with units, abbreviated technical notations | ✅ | ❌ | ❌ | ❌ |
+| Technical Unit | Decimal numbers with units, abbreviated technical notations | ✅ | ❌ | ❌ | ❌ | ❌ |
 
 <details>
 <summary><b>Example 1: Financial Expression</b></summary>
@@ -263,6 +283,7 @@ Supertonic is designed to handle complex, real-world text inputs that contain nu
 | ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1-r2scv7XQ1crIDu6QOh3eqVl445W6ap_/view?usp=sharing) |
 | OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1MFDXMjfmsAVOqwPx7iveS0KUJtZvcwxB/view?usp=sharing) |
 | Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1dEHpNzfMUucFTJPQK0k4RcFZvPwQTt09/view?usp=sharing) |
+| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1b69XWBQnSZZ0WZeR3avv7E8mSdoN6p6P/view?usp=sharing) |
 
 </details>
 
@@ -288,6 +309,7 @@ Supertonic is designed to handle complex, real-world text inputs that contain nu
 | ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1ta3r6jFyebmA-sT44l8EaEQcMLVmuOEr/view?usp=sharing) |
 | OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1sskmem9AzHAQ3Hv8DRSZoqX_pye-CXuU/view?usp=sharing) |
 | Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1zx9X8oMsLMXW0Zx_SURoqjju-By2yh_n/view?usp=sharing) |
+| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1ZpGEstZr4hA0EdAWBMCUFFWuAkIpYsVh/view?usp=sharing) |
 
 </details>
 
@@ -313,6 +335,7 @@ Supertonic is designed to handle complex, real-world text inputs that contain nu
 | ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1HAzVXFTZfZm0VEK2laSpsMTxzufcuaxA/view?usp=sharing) |
 | OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/15tjfAmb3GbjP_kmvD7zSdIWkhtAaCPOg/view?usp=sharing) |
 | Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1BCL8n7yligUZyso970ud7Gf5NWb1OhKD/view?usp=sharing) |
+| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1c0c0YM_Qm7XxSk2uSVYLbITgEDTqaVzL/view?usp=sharing) |
 
 </details>
 
@@ -338,11 +361,26 @@ Supertonic is designed to handle complex, real-world text inputs that contain nu
 | ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1_SzfjWJe5YEd0t3R7DztkYhHcI_av48p/view?usp=sharing) |
 | OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1P5BSilj5xFPTV2Xz6yW5jitKZohO9o-6/view?usp=sharing) |
 | Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1GU82SnWC50OvC8CZNjhxvNZFKQb7I9_Y/view?usp=sharing) |
+| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1lUTrxrAQy_viEK2Hlu3KLLtTCe8jvbdV/view?usp=sharing) |
 
 </details>
 
 > **Note:** These samples demonstrate how each system handles text normalization and pronunciation of complex expressions **without requiring pre-processing or phonetic annotations**.
 
+## Built with Supertonic
+
+| Project | Description | Links |
+|---------|-------------|-------|
+| **Read Aloud** | Open-source TTS browser extension | [Chrome](https://chromewebstore.google.com/detail/read-aloud-a-text-to-spee/hdhinadidafjejdhmfkjgnolgimiaplp) · [Edge](https://microsoftedge.microsoft.com/addons/detail/read-aloud-a-text-to-spe/pnfonnnmfjnpfgagnklfaccicnnjcdkm) · [GitHub](https://github.com/ken107/read-aloud) |
+| **PageEcho** | E-Book reader app for iOS | [App Store](https://apps.apple.com/us/app/pageecho/id6755965837) |
+| **VoiceChat** | On-device voice-to-voice LLM chatbot in the browser | [Demo](https://huggingface.co/spaces/RickRossTN/ai-voice-chat) · [GitHub](https://github.com/irelate-ai/voice-chat) |
+| **OmniAvatar** | Talking avatar video generator from photo + speech | [Demo](https://huggingface.co/spaces/alexnasa/OmniAvatar) |
+| **CopiloTTS** | Kotlin Multiplatform TTS SDK via ONNX Runtime | [GitHub](https://github.com/sigmadeltasoftware/CopiloTTS) |
+| **Voice Mixer** | PyQt5 tool for mixing and modifying voice styles | [GitHub](https://github.com/Topping1/Supertonic-Voice-Mixer) |
+| **Supertonic MNN** | Lightweight library based on MNN (fp32/fp16/int8) | [GitHub](https://github.com/vra/supertonic-mnn) · [PyPI](https://pypi.org/project/supertonic-mnn/) |
+| **Transformers.js** | Hugging Face's JS library with Supertonic support | [GitHub PR](https://github.com/huggingface/transformers.js/pull/1459) · [Demo](https://huggingface.co/spaces/webml-community/Supertonic-TTS-WebGPU) |
+| **Pinokio** | 1-click localhost cloud for Mac, Windows, and Linux | [Pinokio](https://pinokio.co/) · [GitHub](https://github.com/SUP3RMASS1VE/SuperTonic-TTS) |
+
 ## Citation
 
 The following papers describe the core technologies used in Supertonic. If you use this system in your research or find these techniques useful, please consider citing the relevant papers:
@@ -393,9 +431,9 @@ This paper describes the self-purification technique for training flow matching
 
 This project's sample code is released under the MIT License. - see the [LICENSE](https://github.com/supertone-inc/supertonic?tab=MIT-1-ov-file) for details.
 
-The accompanying model is released under the OpenRAIL-M License. - see the [LICENSE](https://huggingface.co/Supertone/supertonic/blob/main/LICENSE) file for details.
+The accompanying model is released under the OpenRAIL-M License. - see the [LICENSE](https://huggingface.co/Supertone/supertonic-2/blob/main/LICENSE) file for details.
 
 This model was trained using PyTorch, which is licensed under the BSD 3-Clause License but is not redistributed with this project. - see the [LICENSE](https://docs.pytorch.org/FBGEMM/general/License.html) for details.
 
-Copyright (c) 2025 Supertone Inc.
+Copyright (c) 2026 Supertone Inc.
 

cpp/README.md

@@ -4,6 +4,12 @@ High-performance text-to-speech inference using ONNX Runtime.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -70,15 +76,16 @@ Process multiple voice styles and texts at once:
 ```bash
 ./example_onnx \
   --voice-style ../assets/voice_styles/M1.json,../assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant." \
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 좋아서 한참을 멈춰 서서 들었어요." \
+  --lang en,ko \
   --batch
 ```
 
 This will:
 - Use `--batch` flag to enable batch processing mode
 - Generate speech for 2 different voice-text pairs
-- Use male voice style (M1.json) for the first text
+- Use male voice style (M1.json) for the first English text
-- Use female voice style (F1.json) for the second text
+- Use female voice style (F1.json) for the second Korean text
 - Process both samples in a single batch (automatic text chunking disabled)
 
 ### Example 3: High Quality Inference
@@ -116,14 +123,17 @@ This will:
 |----------|------|---------|-------------|
 | `--onnx-dir` | str | `../assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
+| `--speed` | float | 1.05 | Speech speed factor (higher = faster, lower = slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str | `../assets/voice_styles/M1.json` | Voice style file path(s) (comma-separated for batch) |
 | `--text` | str | (long default text) | Text(s) to synthesize (pipe-separated for batch) |
+| `--lang` | str | `en` | Language(s) for text(s): `en`, `ko`, `es`, `pt`, `fr` (comma-separated for batch) |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (disables automatic text chunking) |
 
 ## Notes
 
 - **Batch Processing**: The number of `--voice-style` files must match the number of `--text` entries
+- **Multilingual Support**: Use `--lang` to specify language(s). Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
 - **Long-Form Inference**: Without `--batch` flag, long texts are automatically chunked and combined into a single audio file with natural pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer

cpp/example_onnx.cpp

@@ -16,6 +16,7 @@ struct Args {
     std::vector<std::string> text = {
         "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."
     };
+    std::vector<std::string> lang = {"en"};
     std::string save_dir = "results";
     bool batch = false;
 };
@@ -41,6 +42,7 @@ Args parseArgs(int argc, char* argv[]) {
         else if (arg == "--n-test" && i + 1 < argc) args.n_test = std::stoi(argv[++i]);
         else if (arg == "--voice-style" && i + 1 < argc) args.voice_style = splitString(argv[++i], ',');
         else if (arg == "--text" && i + 1 < argc) args.text = splitString(argv[++i], '|');
+        else if (arg == "--lang" && i + 1 < argc) args.lang = splitString(argv[++i], ',');
         else if (arg == "--save-dir" && i + 1 < argc) args.save_dir = argv[++i];
         else if (arg == "--batch") args.batch = true;
     }
@@ -58,6 +60,7 @@ int main(int argc, char* argv[]) {
     std::string save_dir = args.save_dir;
     std::vector<std::string> voice_style_paths = args.voice_style;
     std::vector<std::string> text_list = args.text;
+    std::vector<std::string> lang_list = args.lang;
     bool batch = args.batch;
     
     if (voice_style_paths.size() != text_list.size()) {
@@ -87,9 +90,9 @@ int main(int argc, char* argv[]) {
         
         auto result = timer("Generating speech from text", [&]() {
             if (batch) {
-                return text_to_speech->batch(memory_info, text_list, style, total_step, speed);
+                return text_to_speech->batch(memory_info, text_list, lang_list, style, total_step, speed);
             } else {
-                return text_to_speech->call(memory_info, text_list[0], style, total_step, speed);
+                return text_to_speech->call(memory_info, text_list[0], lang_list[0], style, total_step, speed);
             }
         });
         

cpp/helper.cpp

@@ -6,10 +6,14 @@
 #include <random>
 #include <sstream>
 #include <regex>
+#include <unordered_map>
 #include <nlohmann/json.hpp>
 
 using json = nlohmann::json;
 
+// Available languages for multilingual TTS
+const std::vector<std::string> AVAILABLE_LANGS = {"en", "ko", "es", "pt", "fr"};
+
 // Global tensor buffers for memory management
 static std::vector<std::vector<float>> g_tensor_buffers_float;
 static std::vector<std::vector<int64_t>> g_tensor_buffers_int64;
@@ -45,7 +49,7 @@ UnicodeProcessor::UnicodeProcessor(const std::string& unicode_indexer_json_path)
     indexer_ = loadJsonInt64(unicode_indexer_json_path);
 }
 
-std::string UnicodeProcessor::preprocessText(const std::string& text) {
+std::string UnicodeProcessor::preprocessText(const std::string& text, const std::string& lang) {
     // TODO: Need advanced normalizer for better performance
     // NOTE: C++ doesn't have built-in Unicode normalization like Python's NFKD
     // For full Unicode normalization, consider using ICU library
@@ -53,17 +57,8 @@ std::string UnicodeProcessor::preprocessText(const std::string& text) {
     
     std::string result = text;
     
-    // FIXME: this should be fixed for non-English languages
+    // IMPORTANT: Do symbol replacements FIRST (before emoji removal)
-    
+    // to preserve curly quotes and other punctuation that might be matched by emoji patterns
-    // Remove emojis and various Unicode symbols
-    // Using regex to remove common emoji ranges and special symbols
-    // Note: This is a simplified version - full emoji support needs UTF-8 handling
-    std::regex emoji_pattern(
-        "[\xF0\x9F][\x80-\xBF]{2}|"  // Common emoji pattern in UTF-8
-        "[\xE2][\x80-\xBF]{2}|"       // Various symbols
-        "[\xE2][\x98-\x9E][\x80-\xBF]" // More symbols
-    );
-    result = std::regex_replace(result, emoji_pattern, "");
     
     // Replace various dashes and symbols
     struct Replacement {
@@ -75,12 +70,11 @@ std::string UnicodeProcessor::preprocessText(const std::string& text) {
         {"–", "-"},      // en dash
         {"‑", "-"},      // non-breaking hyphen
         {"—", "-"},      // em dash
-        {"¯", " "},      // macron
         {"_", " "},      // underscore
-        { u8"\u201C", "\"" },   // left double quote “
+        { u8"\u201C", "\"" },   // left double quote "
-        { u8"\u201D", "\"" },   // right double quote ”
+        { u8"\u201D", "\"" },   // right double quote "
-        { u8"\u2018", "'"  },   // left single quote ‘
+        { u8"\u2018", "'"  },   // left single quote '
-        { u8"\u2019", "'"  },   // right single quote ’
+        { u8"\u2019", "'"  },   // right single quote '
         {"´", "'"},      // acute accent
         {"`", "'"},      // grave accent
         {"[", " "},      // left bracket
@@ -100,12 +94,12 @@ std::string UnicodeProcessor::preprocessText(const std::string& text) {
         }
     }
     
-    // Remove combining diacritics (common combining marks in UTF-8)
+    // Remove emojis AFTER symbol replacements
-    // FIXME: this should be fixed for non-English languages
+    // Only target actual emoji ranges (4-byte UTF-8 sequences starting with F0 9F)
-    std::regex diacritics_pattern(
+    std::regex emoji_pattern(
-        "[\xCC\xCD][\x80-\xBF]"  // Combining diacritical marks range
+        "[\xF0][\x9F][\x80-\xBF][\x80-\xBF]"  // 4-byte emoji (U+1F000-U+1FFFF)
     );
-    result = std::regex_replace(result, diacritics_pattern, "");
+    result = std::regex_replace(result, emoji_pattern, "");
     
     // Remove special symbols
     const char* special_symbols[] = {"♥", "☆", "♡", "©", "\\"};
@@ -187,14 +181,168 @@ std::string UnicodeProcessor::preprocessText(const std::string& text) {
         }
     }
     
+    // Validate language
+    bool valid_lang = false;
+    for (const auto& available_lang : AVAILABLE_LANGS) {
+        if (lang == available_lang) {
+            valid_lang = true;
+            break;
+        }
+    }
+    if (!valid_lang) {
+        throw std::runtime_error("Invalid language: " + lang + ". Available: en, ko, es, pt, fr");
+    }
+    
+    // Wrap text with language tags
+    result = "<" + lang + ">" + result + "</" + lang + ">";
+    
     return result;
 }
 
+// Hangul syllable decomposition constants (Unicode Standard Annex #15)
+static const uint32_t HANGUL_SBASE = 0xAC00;  // Start of Hangul syllables
+static const uint32_t HANGUL_LBASE = 0x1100;  // Start of Hangul Jamo (leading consonants)
+static const uint32_t HANGUL_VBASE = 0x1161;  // Start of Hangul Jamo (vowels)
+static const uint32_t HANGUL_TBASE = 0x11A7;  // Start of Hangul Jamo (trailing consonants)
+static const int HANGUL_LCOUNT = 19;  // Number of leading consonants
+static const int HANGUL_VCOUNT = 21;  // Number of vowels
+static const int HANGUL_TCOUNT = 28;  // Number of trailing consonants (including none)
+static const int HANGUL_NCOUNT = HANGUL_VCOUNT * HANGUL_TCOUNT;  // 588
+static const int HANGUL_SCOUNT = HANGUL_LCOUNT * HANGUL_NCOUNT;  // 11172
+
+// Latin character NFKD decompositions for Spanish, Portuguese, French
+static const std::unordered_map<uint32_t, std::vector<uint16_t>> LATIN_DECOMPOSITIONS = {
+    // Acute accent
+    {0x00C1, {0x0041, 0x0301}}, // Á → A + ́
+    {0x00C9, {0x0045, 0x0301}}, // É → E + ́
+    {0x00CD, {0x0049, 0x0301}}, // Í → I + ́
+    {0x00D3, {0x004F, 0x0301}}, // Ó → O + ́
+    {0x00DA, {0x0055, 0x0301}}, // Ú → U + ́
+    {0x00E1, {0x0061, 0x0301}}, // á → a + ́
+    {0x00E9, {0x0065, 0x0301}}, // é → e + ́
+    {0x00ED, {0x0069, 0x0301}}, // í → i + ́
+    {0x00F3, {0x006F, 0x0301}}, // ó → o + ́
+    {0x00FA, {0x0075, 0x0301}}, // ú → u + ́
+    // Grave accent
+    {0x00C0, {0x0041, 0x0300}}, // À → A + ̀
+    {0x00C8, {0x0045, 0x0300}}, // È → E + ̀
+    {0x00CC, {0x0049, 0x0300}}, // Ì → I + ̀
+    {0x00D2, {0x004F, 0x0300}}, // Ò → O + ̀
+    {0x00D9, {0x0055, 0x0300}}, // Ù → U + ̀
+    {0x00E0, {0x0061, 0x0300}}, // à → a + ̀
+    {0x00E8, {0x0065, 0x0300}}, // è → e + ̀
+    {0x00EC, {0x0069, 0x0300}}, // ì → i + ̀
+    {0x00F2, {0x006F, 0x0300}}, // ò → o + ̀
+    {0x00F9, {0x0075, 0x0300}}, // ù → u + ̀
+    // Circumflex
+    {0x00C2, {0x0041, 0x0302}}, // Â → A + ̂
+    {0x00CA, {0x0045, 0x0302}}, // Ê → E + ̂
+    {0x00CE, {0x0049, 0x0302}}, // Î → I + ̂
+    {0x00D4, {0x004F, 0x0302}}, // Ô → O + ̂
+    {0x00DB, {0x0055, 0x0302}}, // Û → U + ̂
+    {0x00E2, {0x0061, 0x0302}}, // â → a + ̂
+    {0x00EA, {0x0065, 0x0302}}, // ê → e + ̂
+    {0x00EE, {0x0069, 0x0302}}, // î → i + ̂
+    {0x00F4, {0x006F, 0x0302}}, // ô → o + ̂
+    {0x00FB, {0x0075, 0x0302}}, // û → u + ̂
+    // Tilde
+    {0x00C3, {0x0041, 0x0303}}, // Ã → A + ̃
+    {0x00D1, {0x004E, 0x0303}}, // Ñ → N + ̃
+    {0x00D5, {0x004F, 0x0303}}, // Õ → O + ̃
+    {0x00E3, {0x0061, 0x0303}}, // ã → a + ̃
+    {0x00F1, {0x006E, 0x0303}}, // ñ → n + ̃
+    {0x00F5, {0x006F, 0x0303}}, // õ → o + ̃
+    // Diaeresis
+    {0x00C4, {0x0041, 0x0308}}, // Ä → A + ̈
+    {0x00CB, {0x0045, 0x0308}}, // Ë → E + ̈
+    {0x00CF, {0x0049, 0x0308}}, // Ï → I + ̈
+    {0x00D6, {0x004F, 0x0308}}, // Ö → O + ̈
+    {0x00DC, {0x0055, 0x0308}}, // Ü → U + ̈
+    {0x00E4, {0x0061, 0x0308}}, // ä → a + ̈
+    {0x00EB, {0x0065, 0x0308}}, // ë → e + ̈
+    {0x00EF, {0x0069, 0x0308}}, // ï → i + ̈
+    {0x00F6, {0x006F, 0x0308}}, // ö → o + ̈
+    {0x00FC, {0x0075, 0x0308}}, // ü → u + ̈
+    // Cedilla
+    {0x00C7, {0x0043, 0x0327}}, // Ç → C + ̧
+    {0x00E7, {0x0063, 0x0327}}, // ç → c + ̧
+};
+
+// Decompose a character using NFKD (Hangul + Latin accented)
+static void decomposeCharacter(uint32_t codepoint, std::vector<uint16_t>& output) {
+    // Check Hangul syllables first
+    if (codepoint >= HANGUL_SBASE && codepoint < HANGUL_SBASE + HANGUL_SCOUNT) {
+        // Decompose Hangul syllable into Jamo
+        uint32_t sIndex = codepoint - HANGUL_SBASE;
+        uint32_t lIndex = sIndex / HANGUL_NCOUNT;
+        uint32_t vIndex = (sIndex % HANGUL_NCOUNT) / HANGUL_TCOUNT;
+        uint32_t tIndex = sIndex % HANGUL_TCOUNT;
+        
+        output.push_back(static_cast<uint16_t>(HANGUL_LBASE + lIndex));
+        output.push_back(static_cast<uint16_t>(HANGUL_VBASE + vIndex));
+        if (tIndex > 0) {
+            output.push_back(static_cast<uint16_t>(HANGUL_TBASE + tIndex));
+        }
+        return;
+    }
+    
+    // Check Latin decompositions
+    auto it = LATIN_DECOMPOSITIONS.find(codepoint);
+    if (it != LATIN_DECOMPOSITIONS.end()) {
+        for (uint16_t cp : it->second) {
+            output.push_back(cp);
+        }
+        return;
+    }
+    
+    // Keep as-is
+    output.push_back(static_cast<uint16_t>(codepoint & 0xFFFF));
+}
+
 std::vector<uint16_t> UnicodeProcessor::textToUnicodeValues(const std::string& text) {
     std::vector<uint16_t> unicode_values;
-    for (char c : text) {
+    size_t i = 0;
-        unicode_values.push_back(static_cast<uint16_t>(static_cast<unsigned char>(c)));
+    
+    while (i < text.size()) {
+        uint32_t codepoint = 0;
+        unsigned char c = static_cast<unsigned char>(text[i]);
+        
+        if ((c & 0x80) == 0) {
+            // 1-byte ASCII (0xxxxxxx)
+            codepoint = c;
+            i += 1;
+        }
+        else if ((c & 0xE0) == 0xC0 && i + 1 < text.size()) {
+            // 2-byte UTF-8 (110xxxxx 10xxxxxx)
+            codepoint = (c & 0x1F) << 6;
+            codepoint |= (static_cast<unsigned char>(text[i + 1]) & 0x3F);
+            i += 2;
+        }
+        else if ((c & 0xF0) == 0xE0 && i + 2 < text.size()) {
+            // 3-byte UTF-8 (1110xxxx 10xxxxxx 10xxxxxx) - includes Korean
+            codepoint = (c & 0x0F) << 12;
+            codepoint |= (static_cast<unsigned char>(text[i + 1]) & 0x3F) << 6;
+            codepoint |= (static_cast<unsigned char>(text[i + 2]) & 0x3F);
+            i += 3;
+        }
+        else if ((c & 0xF8) == 0xF0 && i + 3 < text.size()) {
+            // 4-byte UTF-8 (11110xxx 10xxxxxx 10xxxxxx 10xxxxxx)
+            codepoint = (c & 0x07) << 18;
+            codepoint |= (static_cast<unsigned char>(text[i + 1]) & 0x3F) << 12;
+            codepoint |= (static_cast<unsigned char>(text[i + 2]) & 0x3F) << 6;
+            codepoint |= (static_cast<unsigned char>(text[i + 3]) & 0x3F);
+            i += 4;
+        }
+        else {
+            // Invalid UTF-8, skip byte
+            i += 1;
+            continue;
+        }
+        
+        // Decompose Hangul syllables and Latin accented characters (NFKD)
+        decomposeCharacter(codepoint, unicode_values);
     }
+    
     return unicode_values;
 }
 
@@ -206,25 +354,31 @@ std::vector<std::vector<std::vector<float>>> UnicodeProcessor::getTextMask(
 
 void UnicodeProcessor::call(
     const std::vector<std::string>& text_list,
+    const std::vector<std::string>& lang_list,
     std::vector<std::vector<int64_t>>& text_ids,
     std::vector<std::vector<std::vector<float>>>& text_mask
 ) {
     std::vector<std::string> processed_texts;
-    for (const auto& text : text_list) {
+    for (size_t i = 0; i < text_list.size(); i++) {
-        processed_texts.push_back(preprocessText(text));
+        processed_texts.push_back(preprocessText(text_list[i], lang_list[i]));
     }
     
+    // Convert texts to unicode values first to get correct character counts
+    std::vector<std::vector<uint16_t>> all_unicode_vals;
     std::vector<int64_t> text_ids_lengths;
     for (const auto& text : processed_texts) {
-        text_ids_lengths.push_back(static_cast<int64_t>(text.length()));
+        auto unicode_vals = textToUnicodeValues(text);
+        // Use number of Unicode codepoints, not bytes
+        text_ids_lengths.push_back(static_cast<int64_t>(unicode_vals.size()));
+        all_unicode_vals.push_back(std::move(unicode_vals));
     }
     
     int64_t max_len = *std::max_element(text_ids_lengths.begin(), text_ids_lengths.end());
     
     text_ids.resize(text_list.size());
-    for (size_t i = 0; i < processed_texts.size(); i++) {
+    for (size_t i = 0; i < all_unicode_vals.size(); i++) {
         text_ids[i].resize(max_len, 0);
-        auto unicode_vals = textToUnicodeValues(processed_texts[i]);
+        const auto& unicode_vals = all_unicode_vals[i];
         for (size_t j = 0; j < unicode_vals.size(); j++) {
             if (unicode_vals[j] < indexer_.size()) {
                 text_ids[i][j] = indexer_[unicode_vals[j]];
@@ -315,6 +469,7 @@ void TextToSpeech::sampleNoisyLatent(
 TextToSpeech::SynthesisResult TextToSpeech::_infer(
     Ort::MemoryInfo& memory_info,
     const std::vector<std::string>& text_list,
+    const std::vector<std::string>& lang_list,
     const Style& style,
     int total_step,
     float speed
@@ -328,7 +483,7 @@ TextToSpeech::SynthesisResult TextToSpeech::_infer(
     // Process text
     std::vector<std::vector<int64_t>> text_ids;
     std::vector<std::vector<std::vector<float>>> text_mask;
-    text_processor_->call(text_list, text_ids, text_mask);
+    text_processor_->call(text_list, lang_list, text_ids, text_mask);
     
     std::vector<int64_t> text_ids_shape = {bsz, static_cast<int64_t>(text_ids[0].size())};
     std::vector<int64_t> text_mask_shape = {bsz, 1, static_cast<int64_t>(text_mask[0][0].size())};
@@ -530,6 +685,7 @@ TextToSpeech::SynthesisResult TextToSpeech::_infer(
 TextToSpeech::SynthesisResult TextToSpeech::call(
     Ort::MemoryInfo& memory_info,
     const std::string& text,
+    const std::string& lang,
     const Style& style,
     int total_step,
     float speed,
@@ -539,12 +695,13 @@ TextToSpeech::SynthesisResult TextToSpeech::call(
         throw std::runtime_error("Single speaker text to speech only supports single style");
     }
     
-    auto text_list = chunkText(text);
+    int max_len = (lang == "ko") ? 120 : 300;
+    auto text_list = chunkText(text, max_len);
     std::vector<float> wav_cat;
     float dur_cat = 0.0f;
     
     for (const auto& chunk : text_list) {
-        auto result = _infer(memory_info, {chunk}, style, total_step, speed);
+        auto result = _infer(memory_info, {chunk}, {lang}, style, total_step, speed);
         
         if (wav_cat.empty()) {
             wav_cat = result.wav;
@@ -568,11 +725,12 @@ TextToSpeech::SynthesisResult TextToSpeech::call(
 TextToSpeech::SynthesisResult TextToSpeech::batch(
     Ort::MemoryInfo& memory_info,
     const std::vector<std::string>& text_list,
+    const std::vector<std::string>& lang_list,
     const Style& style,
     int total_step,
     float speed
 ) {
-    return _infer(memory_info, text_list, style, total_step, speed);
+    return _infer(memory_info, text_list, lang_list, style, total_step, speed);
 }
 
 // ============================================================================
@@ -911,15 +1069,43 @@ std::vector<int64_t> loadJsonInt64(const std::string& file_path) {
 
 std::string sanitizeFilename(const std::string& text, int max_len) {
     std::string result;
-    int count = 0;
+    int char_count = 0;
-    for (char c : text) {
+    size_t i = 0;
-        if (count >= max_len) break;
+    
-        if (std::isalnum(static_cast<unsigned char>(c))) {
+    while (i < text.size() && char_count < max_len) {
-            result += c;
+        unsigned char c = static_cast<unsigned char>(text[i]);
-        } else {
+        
-            result += '_';
+        // Check if it's ASCII alphanumeric or underscore
+        if (std::isalnum(c) || c == '_') {
+            result += text[i];
+            i++;
+            char_count++;
+        }
+        // Check for UTF-8 multi-byte sequences (preserve Unicode letters/numbers)
+        else if ((c & 0xE0) == 0xC0 && i + 1 < text.size()) {
+            // 2-byte UTF-8 sequence
+            result += text.substr(i, 2);
+            i += 2;
+            char_count++;
+        }
+        else if ((c & 0xF0) == 0xE0 && i + 2 < text.size()) {
+            // 3-byte UTF-8 sequence (includes Korean, Japanese, Chinese)
+            result += text.substr(i, 3);
+            i += 3;
+            char_count++;
+        }
+        else if ((c & 0xF8) == 0xF0 && i + 3 < text.size()) {
+            // 4-byte UTF-8 sequence
+            result += text.substr(i, 4);
+            i += 4;
+            char_count++;
+        }
+        else {
+            // Replace other characters with underscore
+            result += '_';
+            i++;
+            char_count++;
         }
-        count++;
     }
     return result;
 }

cpp/helper.h

@@ -8,6 +8,9 @@
 #include <chrono>
 #include <onnxruntime_cxx_api.h>
 
+// Available languages for multilingual TTS
+extern const std::vector<std::string> AVAILABLE_LANGS;
+
 /**
  * Configuration structure
  */
@@ -33,6 +36,7 @@ public:
     // Process text list to text IDs and mask
     void call(
         const std::vector<std::string>& text_list,
+        const std::vector<std::string>& lang_list,
         std::vector<std::vector<int64_t>>& text_ids,
         std::vector<std::vector<std::vector<float>>>& text_mask
     );
@@ -40,7 +44,7 @@ public:
 private:
     std::vector<int64_t> indexer_;
     
-    std::string preprocessText(const std::string& text);
+    std::string preprocessText(const std::string& text, const std::string& lang);
     std::vector<uint16_t> textToUnicodeValues(const std::string& text);
     std::vector<std::vector<std::vector<float>>> getTextMask(
         const std::vector<int64_t>& text_ids_lengths
@@ -89,6 +93,7 @@ public:
     SynthesisResult call(
         Ort::MemoryInfo& memory_info,
         const std::string& text,
+        const std::string& lang,
         const Style& style,
         int total_step,
         float speed = 1.05f,
@@ -98,6 +103,7 @@ public:
     SynthesisResult batch(
         Ort::MemoryInfo& memory_info,
         const std::vector<std::string>& text_list,
+        const std::vector<std::string>& lang_list,
         const Style& style,
         int total_step,
         float speed = 1.05f
@@ -109,6 +115,7 @@ private:
     SynthesisResult _infer(
         Ort::MemoryInfo& memory_info,
         const std::vector<std::string>& text_list,
+        const std::vector<std::string>& lang_list,
         const Style& style,
         int total_step,
         float speed = 1.05f

csharp/ExampleONNX.cs

@@ -19,6 +19,7 @@ namespace Supertonic
             { 
                 "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen." 
             };
+            public List<string> Lang { get; set; } = new List<string> { "en" };
             public string SaveDir { get; set; } = "results";
             public bool Batch { get; set; } = false;
         }
@@ -55,6 +56,9 @@ namespace Supertonic
                     case "--text" when i + 1 < args.Length:
                         result.Text = args[++i].Split('|').ToList();
                         break;
+                    case "--lang" when i + 1 < args.Length:
+                        result.Lang = args[++i].Split(',').ToList();
+                        break;
                     case "--save-dir" when i + 1 < args.Length:
                         result.SaveDir = args[++i];
                         break;
@@ -76,6 +80,7 @@ namespace Supertonic
             string saveDir = parsedArgs.SaveDir;
             var voiceStylePaths = parsedArgs.VoiceStyle;
             var textList = parsedArgs.Text;
+            var langList = parsedArgs.Lang;
             bool batch = parsedArgs.Batch;
 
             if (voiceStylePaths.Count != textList.Count)
@@ -101,11 +106,11 @@ namespace Supertonic
                 {
                     if (batch)
                     {
-                        return textToSpeech.Batch(textList, style, totalStep, speed);
+                        return textToSpeech.Batch(textList, langList, style, totalStep, speed);
                     }
                     else
                     {
-                        return textToSpeech.Call(textList[0], style, totalStep, speed);
+                        return textToSpeech.Call(textList[0], langList[0], style, totalStep, speed);
                     }
                 });
 

csharp/Helper.cs

@@ -10,6 +10,12 @@ using Microsoft.ML.OnnxRuntime.Tensors;
 
 namespace Supertonic
 {
+    // Available languages for multilingual TTS
+    public static class Languages
+    {
+        public static readonly string[] Available = { "en", "ko", "es", "pt", "fr" };
+    }
+
     // ============================================================================
     // Configuration classes
     // ============================================================================
@@ -118,13 +124,11 @@ namespace Supertonic
             return result.ToString();
         }
 
-        private string PreprocessText(string text)
+        private string PreprocessText(string text, string lang)
         {
             // TODO: Need advanced normalizer for better performance
             text = text.Normalize(NormalizationForm.FormKD);
 
-            // FIXME: this should be fixed for non-English languages
-
             // Remove emojis (wide Unicode range)
             // C# doesn't support \u{...} syntax in regex, so we use character filtering instead
             text = RemoveEmojis(text);
@@ -135,7 +139,6 @@ namespace Supertonic
                 {"–", "-"},      // en dash
                 {"‑", "-"},      // non-breaking hyphen
                 {"—", "-"},      // em dash
-                {"¯", " "},      // macron
                 {"_", " "},      // underscore
                 {"\u201C", "\""},     // left double quote
                 {"\u201D", "\""},     // right double quote
@@ -157,9 +160,6 @@ namespace Supertonic
                 text = text.Replace(kvp.Key, kvp.Value);
             }
 
-            // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-            text = Regex.Replace(text, @"[\u0302\u0303\u0304\u0305\u0306\u0307\u0308\u030A\u030B\u030C\u0327\u0328\u0329\u032A\u032B\u032C\u032D\u032E\u032F]", "");
-
             // Remove special symbols
             text = Regex.Replace(text, @"[♥☆♡©\\]", "");
 
@@ -208,6 +208,15 @@ namespace Supertonic
                 text += ".";
             }
 
+            // Validate language
+            if (!Languages.Available.Contains(lang))
+            {
+                throw new ArgumentException($"Invalid language: {lang}. Available: {string.Join(", ", Languages.Available)}");
+            }
+
+            // Wrap text with language tags
+            text = $"<{lang}>" + text + $"</{lang}>";
+
             return text;
         }
 
@@ -221,9 +230,9 @@ namespace Supertonic
             return Helper.LengthToMask(textIdsLengths);
         }
 
-        public (long[][] textIds, float[][][] textMask) Call(List<string> textList)
+        public (long[][] textIds, float[][][] textMask) Call(List<string> textList, List<string> langList)
         {
-            var processedTexts = textList.Select(t => PreprocessText(t)).ToList();
+            var processedTexts = textList.Select((t, i) => PreprocessText(t, langList[i])).ToList();
             var textIdsLengths = processedTexts.Select(t => (long)t.Length).ToArray();
             long maxLen = textIdsLengths.Max();
 
@@ -328,7 +337,7 @@ namespace Supertonic
             return (noisyLatent, latentMask);
         }
 
-        private (float[] wav, float[] duration) _Infer(List<string> textList, Style style, int totalStep, float speed = 1.05f)
+        private (float[] wav, float[] duration) _Infer(List<string> textList, List<string> langList, Style style, int totalStep, float speed = 1.05f)
         {
             int bsz = textList.Count;
             if (bsz != style.TtlShape[0])
@@ -337,7 +346,7 @@ namespace Supertonic
             }
 
             // Process text
-            var (textIds, textMask) = _textProcessor.Call(textList);
+            var (textIds, textMask) = _textProcessor.Call(textList, langList);
             var textIdsShape = new long[] { bsz, textIds[0].Length };
             var textMaskShape = new long[] { bsz, 1, textMask[0][0].Length };
 
@@ -424,20 +433,21 @@ namespace Supertonic
             return (wavTensor.ToArray(), durOnnx);
         }
 
-        public (float[] wav, float[] duration) Call(string text, Style style, int totalStep, float speed = 1.05f, float silenceDuration = 0.3f)
+        public (float[] wav, float[] duration) Call(string text, string lang, Style style, int totalStep, float speed = 1.05f, float silenceDuration = 0.3f)
         {
             if (style.TtlShape[0] != 1)
             {
                 throw new ArgumentException("Single speaker text to speech only supports single style");
             }
 
-            var textList = Helper.ChunkText(text);
+            int maxLen = lang == "ko" ? 120 : 300;
+            var textList = Helper.ChunkText(text, maxLen);
             var wavCat = new List<float>();
             float durCat = 0.0f;
 
             foreach (var chunk in textList)
             {
-                var (wav, duration) = _Infer(new List<string> { chunk }, style, totalStep, speed);
+                var (wav, duration) = _Infer(new List<string> { chunk }, new List<string> { lang }, style, totalStep, speed);
 
                 if (wavCat.Count == 0)
                 {
@@ -457,9 +467,9 @@ namespace Supertonic
             return (wavCat.ToArray(), new float[] { durCat });
         }
 
-        public (float[] wav, float[] duration) Batch(List<string> textList, Style style, int totalStep, float speed = 1.05f)
+        public (float[] wav, float[] duration) Batch(List<string> textList, List<string> langList, Style style, int totalStep, float speed = 1.05f)
         {
-            return _Infer(textList, style, totalStep, speed);
+            return _Infer(textList, langList, style, totalStep, speed);
         }
     }
 

csharp/README.md

@@ -4,6 +4,12 @@ This guide provides examples for running TTS inference using `ExampleONNX.cs`.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -41,15 +47,16 @@ Process multiple voice styles and texts at once:
 ```bash
 dotnet run -- \
   --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant." \
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 좋아서 한참을 멈춰 서서 들었어요." \
+  --lang en,ko \
   --batch
 ```
 
 This will:
 - Use `--batch` flag to enable batch processing mode
 - Generate speech for 2 different voice-text pairs
-- Use male voice style (M1.json) for the first text
+- Use male voice style (M1.json) for the first English text
-- Use female voice style (F1.json) for the second text
+- Use female voice style (F1.json) for the second Korean text
 - Process both samples in a single batch (automatic text chunking disabled)
 
 ### Example 3: High Quality Inference
@@ -88,15 +95,18 @@ This will:
 | `--use-gpu` | flag | False | Use GPU for inference (not supported yet) |
 | `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
+| `--speed` | float | 1.05 | Speech speed factor (higher = faster, lower = slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) (comma-separated) |
 | `--text` | str+ | (long default text) | Text(s) to synthesize (pipe-separated: `|`) |
+| `--lang` | str+ | `en` | Language(s) for text(s): `en`, `ko`, `es`, `pt`, `fr` (comma-separated) |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (disables automatic text chunking) |
 
 ## Notes
 
 - **Batch Processing**: The number of `--voice-style` files must match the number of `--text` entries
+- **Multilingual Support**: Use `--lang` to specify language(s). Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
 - **Long-Form Inference**: Without `--batch` flag, long texts are automatically chunked and combined into a single audio file with natural pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

flutter/README.md

@@ -1,14 +1,29 @@
 # Supertonic Flutter Example
 
-This example demonstrates how to use Supertonic in a Flutter application using ONNX Runtime.
+This example demonstrates how to use Supertonic 2 in a Flutter application using ONNX Runtime.
 
 > **Note:** This project uses the `flutter_onnxruntime` package ([https://pub.dev/packages/flutter_onnxruntime](https://pub.dev/packages/flutter_onnxruntime)). At the moment, only the macOS platform has been tested. Although the flutter_onnxruntime package supports several other platforms, they have not been tested in this project yet and may require additional verification.
 
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Added and tested macos support.
 
+## Multilingual Support
+
+Supertonic 2 supports multiple languages. Select the appropriate language from the dropdown:
+- **English (en)**: Default language
+- **한국어 (ko)**: Korean
+- **Español (es)**: Spanish
+- **Português (pt)**: Portuguese
+- **Français (fr)**: French
+
 ## Requirements
 
 - Flutter SDK version ^3.5.0

flutter/lib/helper.dart

@@ -11,6 +11,205 @@ final logger = Logger(
   printer: PrettyPrinter(methodCount: 0, errorMethodCount: 5, lineLength: 80),
 );
 
+// Available languages for multilingual TTS
+const List<String> availableLangs = ['en', 'ko', 'es', 'pt', 'fr'];
+
+bool isValidLang(String lang) => availableLangs.contains(lang);
+
+// Hangul Jamo constants for NFKD decomposition
+const int _hangulSyllableBase = 0xAC00;
+const int _hangulSyllableEnd = 0xD7A3;
+const int _leadingJamoBase = 0x1100;
+const int _vowelJamoBase = 0x1161;
+const int _trailingJamoBase = 0x11A7;
+const int _vowelCount = 21;
+const int _trailingCount = 28;
+
+/// Decompose a Hangul syllable into Jamo (NFKD-like decomposition)
+List<int> _decomposeHangulSyllable(int codePoint) {
+  if (codePoint < _hangulSyllableBase || codePoint > _hangulSyllableEnd) {
+    return [codePoint];
+  }
+
+  final syllableIndex = codePoint - _hangulSyllableBase;
+  final leadingIndex = syllableIndex ~/ (_vowelCount * _trailingCount);
+  final vowelIndex =
+      (syllableIndex % (_vowelCount * _trailingCount)) ~/ _trailingCount;
+  final trailingIndex = syllableIndex % _trailingCount;
+
+  final result = <int>[
+    _leadingJamoBase + leadingIndex,
+    _vowelJamoBase + vowelIndex,
+  ];
+
+  if (trailingIndex > 0) {
+    result.add(_trailingJamoBase + trailingIndex);
+  }
+
+  return result;
+}
+
+/// Common Latin character decompositions (NFKD) for es, pt, fr
+const Map<int, List<int>> _latinDecompositions = {
+  // Uppercase with acute accent
+  0x00C1: [0x0041, 0x0301], // Á → A + ́
+  0x00C9: [0x0045, 0x0301], // É → E + ́
+  0x00CD: [0x0049, 0x0301], // Í → I + ́
+  0x00D3: [0x004F, 0x0301], // Ó → O + ́
+  0x00DA: [0x0055, 0x0301], // Ú → U + ́
+  // Lowercase with acute accent
+  0x00E1: [0x0061, 0x0301], // á → a + ́
+  0x00E9: [0x0065, 0x0301], // é → e + ́
+  0x00ED: [0x0069, 0x0301], // í → i + ́
+  0x00F3: [0x006F, 0x0301], // ó → o + ́
+  0x00FA: [0x0075, 0x0301], // ú → u + ́
+  // Grave accent
+  0x00C0: [0x0041, 0x0300], // À → A + ̀
+  0x00C8: [0x0045, 0x0300], // È → E + ̀
+  0x00CC: [0x0049, 0x0300], // Ì → I + ̀
+  0x00D2: [0x004F, 0x0300], // Ò → O + ̀
+  0x00D9: [0x0055, 0x0300], // Ù → U + ̀
+  0x00E0: [0x0061, 0x0300], // à → a + ̀
+  0x00E8: [0x0065, 0x0300], // è → e + ̀
+  0x00EC: [0x0069, 0x0300], // ì → i + ̀
+  0x00F2: [0x006F, 0x0300], // ò → o + ̀
+  0x00F9: [0x0075, 0x0300], // ù → u + ̀
+  // Circumflex
+  0x00C2: [0x0041, 0x0302], // Â → A + ̂
+  0x00CA: [0x0045, 0x0302], // Ê → E + ̂
+  0x00CE: [0x0049, 0x0302], // Î → I + ̂
+  0x00D4: [0x004F, 0x0302], // Ô → O + ̂
+  0x00DB: [0x0055, 0x0302], // Û → U + ̂
+  0x00E2: [0x0061, 0x0302], // â → a + ̂
+  0x00EA: [0x0065, 0x0302], // ê → e + ̂
+  0x00EE: [0x0069, 0x0302], // î → i + ̂
+  0x00F4: [0x006F, 0x0302], // ô → o + ̂
+  0x00FB: [0x0075, 0x0302], // û → u + ̂
+  // Tilde
+  0x00C3: [0x0041, 0x0303], // Ã → A + ̃
+  0x00D1: [0x004E, 0x0303], // Ñ → N + ̃
+  0x00D5: [0x004F, 0x0303], // Õ → O + ̃
+  0x00E3: [0x0061, 0x0303], // ã → a + ̃
+  0x00F1: [0x006E, 0x0303], // ñ → n + ̃
+  0x00F5: [0x006F, 0x0303], // õ → o + ̃
+  // Diaeresis/Umlaut
+  0x00C4: [0x0041, 0x0308], // Ä → A + ̈
+  0x00CB: [0x0045, 0x0308], // Ë → E + ̈
+  0x00CF: [0x0049, 0x0308], // Ï → I + ̈
+  0x00D6: [0x004F, 0x0308], // Ö → O + ̈
+  0x00DC: [0x0055, 0x0308], // Ü → U + ̈
+  0x00E4: [0x0061, 0x0308], // ä → a + ̈
+  0x00EB: [0x0065, 0x0308], // ë → e + ̈
+  0x00EF: [0x0069, 0x0308], // ï → i + ̈
+  0x00F6: [0x006F, 0x0308], // ö → o + ̈
+  0x00FC: [0x0075, 0x0308], // ü → u + ̈
+  // Cedilla
+  0x00C7: [0x0043, 0x0327], // Ç → C + ̧
+  0x00E7: [0x0063, 0x0327], // ç → c + ̧
+};
+
+/// Apply NFKD-like decomposition (Hangul + Latin accented characters)
+String _applyNfkdDecomposition(String text) {
+  final result = <int>[];
+  for (final codePoint in text.runes) {
+    // Check Hangul first
+    if (codePoint >= _hangulSyllableBase && codePoint <= _hangulSyllableEnd) {
+      result.addAll(_decomposeHangulSyllable(codePoint));
+    }
+    // Check Latin decomposition
+    else if (_latinDecompositions.containsKey(codePoint)) {
+      result.addAll(_latinDecompositions[codePoint]!);
+    }
+    // Keep as-is
+    else {
+      result.add(codePoint);
+    }
+  }
+  return String.fromCharCodes(result);
+}
+
+String preprocessText(String text, String lang) {
+  // Apply NFKD-like decomposition (especially for Hangul syllables → Jamo)
+  text = _applyNfkdDecomposition(text);
+
+  // Remove emojis
+  text = text.replaceAll(
+      RegExp(
+        r'[\u{1F600}-\u{1F64F}]|[\u{1F300}-\u{1F5FF}]|[\u{1F680}-\u{1F6FF}]|'
+        r'[\u{1F700}-\u{1F77F}]|[\u{1F780}-\u{1F7FF}]|[\u{1F800}-\u{1F8FF}]|'
+        r'[\u{1F900}-\u{1F9FF}]|[\u{1FA00}-\u{1FA6F}]|[\u{1FA70}-\u{1FAFF}]|'
+        r'[\u{2600}-\u{26FF}]|[\u{2700}-\u{27BF}]|[\u{1F1E6}-\u{1F1FF}]',
+        unicode: true,
+      ),
+      '');
+
+  // Replace various dashes and symbols
+  const replacements = {
+    '–': '-',
+    '‑': '-',
+    '—': '-',
+    '_': ' ',
+    '\u201C': '"',
+    '\u201D': '"',
+    '\u2018': "'",
+    '\u2019': "'",
+    '´': "'",
+    '`': "'",
+    '[': ' ',
+    ']': ' ',
+    '|': ' ',
+    '/': ' ',
+    '#': ' ',
+    '→': ' ',
+    '←': ' ',
+  };
+  for (final entry in replacements.entries) {
+    text = text.replaceAll(entry.key, entry.value);
+  }
+
+  // Remove special symbols
+  text = text.replaceAll(RegExp(r'[♥☆♡©\\]'), '');
+
+  // Replace known expressions
+  text = text.replaceAll('@', ' at ');
+  text = text.replaceAll('e.g.,', 'for example, ');
+  text = text.replaceAll('i.e.,', 'that is, ');
+
+  // Fix spacing around punctuation
+  text = text.replaceAll(' ,', ',');
+  text = text.replaceAll(' .', '.');
+  text = text.replaceAll(' !', '!');
+  text = text.replaceAll(' ?', '?');
+  text = text.replaceAll(' ;', ';');
+  text = text.replaceAll(' :', ':');
+  text = text.replaceAll(" '", "'");
+
+  // Remove duplicate quotes
+  while (text.contains('""')) text = text.replaceAll('""', '"');
+  while (text.contains("''")) text = text.replaceAll("''", "'");
+  while (text.contains('``')) text = text.replaceAll('``', '`');
+
+  // Remove extra spaces
+  text = text.replaceAll(RegExp(r'\s+'), ' ').trim();
+
+  // Add period if needed
+  if (text.isNotEmpty &&
+      !RegExp(r'[.!?;:,\x27\x22\u2018\u2019)\]}…。」』】〉》›»]$').hasMatch(text)) {
+    text += '.';
+  }
+
+  // Validate language
+  if (!isValidLang(lang)) {
+    throw ArgumentError(
+        'Invalid language: $lang. Available: ${availableLangs.join(", ")}');
+  }
+
+  // Wrap text with language tags
+  text = '<$lang>$text</$lang>';
+
+  return text;
+}
+
 class UnicodeProcessor {
   final Map<int, int> indexer;
 
@@ -34,11 +233,17 @@ class UnicodeProcessor {
     return UnicodeProcessor._(indexer);
   }
 
-  Map<String, dynamic> call(List<String> textList) {
+  Map<String, dynamic> call(List<String> textList, List<String> langList) {
-    final lengths = textList.map((t) => t.length).toList();
+    // Preprocess texts with language tags
+    final processedTexts = <String>[];
+    for (var i = 0; i < textList.length; i++) {
+      processedTexts.add(preprocessText(textList[i], langList[i]));
+    }
+
+    final lengths = processedTexts.map((t) => t.runes.length).toList();
     final maxLen = lengths.reduce(math.max);
 
-    final textIds = textList.map((text) {
+    final textIds = processedTexts.map((text) {
       final row = List<int>.filled(maxLen, 0);
       final runes = text.runes.toList();
       for (var i = 0; i < runes.length; i++) {
@@ -77,14 +282,18 @@ class TextToSpeech {
         chunkCompressFactor = cfgs['ttl']['chunk_compress_factor'],
         ldim = cfgs['ttl']['latent_dim'];
 
-  Future<Map<String, dynamic>> call(String text, Style style, int totalStep,
+  Future<Map<String, dynamic>> call(
+      String text, String lang, Style style, int totalStep,
       {double speed = 1.05, double silenceDuration = 0.3}) async {
-    final chunks = _chunkText(text);
+    final maxLen = lang == 'ko' ? 120 : 300;
+    final chunks = _chunkText(text, maxLen: maxLen);
+    final langList = List.filled(chunks.length, lang);
     List<double>? wavCat;
     double durCat = 0;
 
-    for (final chunk in chunks) {
+    for (var i = 0; i < chunks.length; i++) {
-      final result = await _infer([chunk], style, totalStep, speed: speed);
+      final result = await _infer([chunks[i]], [langList[i]], style, totalStep,
+          speed: speed);
       final wav = _safeCast<double>(result['wav']);
       final duration = _safeCast<double>(result['duration']);
 
@@ -108,10 +317,10 @@ class TextToSpeech {
   }
 
   Future<Map<String, dynamic>> _infer(
-      List<String> textList, Style style, int totalStep,
+      List<String> textList, List<String> langList, Style style, int totalStep,
       {double speed = 1.05}) async {
     final bsz = textList.length;
-    final result = textProcessor.call(textList);
+    final result = textProcessor.call(textList, langList);
 
     final textIdsRaw = result['textIds'];
     final textIds = textIdsRaw is List<List<int>>

flutter/lib/main.dart

@@ -14,7 +14,7 @@ class SupertonicApp extends StatelessWidget {
   @override
   Widget build(BuildContext context) {
     return MaterialApp(
-      title: 'Supertonic',
+      title: 'Supertonic 2',
       theme: ThemeData(
         colorScheme: ColorScheme.fromSeed(seedColor: Colors.deepPurple),
         useMaterial3: true,
@@ -44,6 +44,7 @@ class _TTSPageState extends State<TTSPage> {
   String _status = 'Not initialized';
   int _totalSteps = 5;
   double _speed = 1.05;
+  String _selectedLang = 'en';
   bool _isPlaying = false;
   String? _lastGeneratedFilePath;
 
@@ -119,6 +120,7 @@ class _TTSPageState extends State<TTSPage> {
     try {
       final result = await _textToSpeech!.call(
         _textController.text,
+        _selectedLang,
         _style!,
         _totalSteps,
         speed: _speed,
@@ -208,7 +210,7 @@ class _TTSPageState extends State<TTSPage> {
     return Scaffold(
       appBar: AppBar(
         backgroundColor: Theme.of(context).colorScheme.inversePrimary,
-        title: const Text('Supertonic'),
+        title: const Text('Supertonic 2'),
       ),
       body: Padding(
         padding: const EdgeInsets.all(16.0),
@@ -310,6 +312,31 @@ class _TTSPageState extends State<TTSPage> {
                 ),
               ],
             ),
+            const SizedBox(height: 12),
+
+            // Language selector
+            Row(
+              children: [
+                const Expanded(flex: 2, child: Text('Language:')),
+                Expanded(
+                  flex: 3,
+                  child: DropdownButton<String>(
+                    value: _selectedLang,
+                    isExpanded: true,
+                    items: const [
+                      DropdownMenuItem(value: 'en', child: Text('English')),
+                      DropdownMenuItem(value: 'ko', child: Text('한국어')),
+                      DropdownMenuItem(value: 'es', child: Text('Español')),
+                      DropdownMenuItem(value: 'pt', child: Text('Português')),
+                      DropdownMenuItem(value: 'fr', child: Text('Français')),
+                    ],
+                    onChanged: _isLoading || _isGenerating
+                        ? null
+                        : (value) => setState(() => _selectedLang = value!),
+                  ),
+                ),
+              ],
+            ),
             const SizedBox(height: 24),
 
             // Generate button

flutter/macos/Podfile.lock

@@ -41,11 +41,11 @@ EXTERNAL SOURCES:
     :path: Flutter/ephemeral/.symlinks/plugins/objective_c/macos
 
 SPEC CHECKSUMS:
-  audio_session: eaca2512cf2b39212d724f35d11f46180ad3a33e
+  audio_session: 728ae3823d914f809c485d390274861a24b0904e
-  flutter_onnxruntime: 546c7c7630c9259f59021319639b30bdaff148c2
+  flutter_onnxruntime: e6887abc1032d3e5c92f84b912ad42c33e9ce1c9
   FlutterMacOS: d0db08ddef1a9af05a5ec4b724367152bb0500b1
-  just_audio: 4e391f57b79cad2b0674030a00453ca5ce817eed
+  just_audio: a42c63806f16995daf5b219ae1d679deb76e6a79
-  objective_c: ec13431e45ba099cb734eb2829a5c1cd37986cba
+  objective_c: e5f8194456e8fc943e034d1af00510a1bc29c067
   onnxruntime-c: ac65025f01072d25d7d394a2b43ac30d9397b260
   onnxruntime-objc: 5fa03134356d47b642ec85b1023d9907a123d201
 

go/README.md

@@ -4,6 +4,12 @@ This guide provides examples for running TTS inference using `example_onnx.go`.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -83,13 +89,14 @@ Process multiple voice styles and texts at once:
 go run example_onnx.go helper.go \
   --batch \
   -voice-style "assets/voice_styles/M1.json,assets/voice_styles/F1.json" \
-  -text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."
+  -text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요." \
+  -lang "en,ko"
 ```
 
 This will:
-- Generate speech for 2 different voice-text pairs
+- Generate speech for 2 different voice-text-language pairs
-- Use male voice (M1.json) for the first text
+- Use male voice (M1.json) for the first text in English
-- Use female voice (F1.json) for the second text
+- Use female voice (F1.json) for the second text in Korean
 - Process both samples in a single batch
 
 ### Example 3: High Quality Inference
@@ -132,12 +139,14 @@ This will:
 | `-n-test` | int | 4 | Number of times to generate each sample |
 | `-voice-style` | str | `assets/voice_styles/M1.json` | Voice style file path(s), comma-separated |
 | `-text` | str | (long default text) | Text(s) to synthesize, pipe-separated |
+| `-lang` | str | `en` | Language(s) for synthesis, comma-separated (en, ko, es, pt, fr) |
 | `-save-dir` | str | `results` | Output directory |
 | `--batch` | flag | false | Enable batch mode (multiple text-style pairs, disables automatic chunking) |
 
 ## Notes
 
-- **Batch Processing**: When using `--batch`, the number of `-voice-style` files must match the number of `-text` entries
+- **Multilingual Support**: Use `-lang` to specify the language for each text. Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
+- **Batch Processing**: When using `--batch`, the number of `-voice-style`, `-text`, and `-lang` entries must match
 - **Automatic Chunking**: Without `--batch`, long texts are automatically split and concatenated with 0.3s pauses
 - **Quality vs Speed**: Higher `-total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

go/example_onnx.go

@@ -19,6 +19,7 @@ type Args struct {
 	nTest       int
 	voiceStyle  []string
 	text        []string
+	lang        []string
 	saveDir     string
 	batch       bool
 }
@@ -34,9 +35,10 @@ func parseArgs() *Args {
 	flag.StringVar(&args.saveDir, "save-dir", "results", "Output directory")
 	flag.BoolVar(&args.batch, "batch", false, "Enable batch mode (multiple text-style pairs)")
 
-	var voiceStyleStr, textStr string
+	var voiceStyleStr, textStr, langStr string
 	flag.StringVar(&voiceStyleStr, "voice-style", "assets/voice_styles/M1.json", "Voice style file path(s), comma-separated")
 	flag.StringVar(&textStr, "text", "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen.", "Text(s) to synthesize, pipe-separated")
+	flag.StringVar(&langStr, "lang", "en", "Language(s) for synthesis, comma-separated (en, ko, es, pt, fr)")
 
 	flag.Parse()
 
@@ -56,6 +58,14 @@ func parseArgs() *Args {
 		}
 	}
 
+	// Parse comma-separated lang
+	if langStr != "" {
+		args.lang = strings.Split(langStr, ",")
+		for i := range args.lang {
+			args.lang[i] = strings.TrimSpace(args.lang[i])
+		}
+	}
+
 	return args
 }
 
@@ -70,6 +80,7 @@ func main() {
 	saveDir := args.saveDir
 	voiceStylePaths := args.voiceStyle
 	textList := args.text
+	langList := args.lang
 	batch := args.batch
 
 	if batch {
@@ -78,6 +89,11 @@ func main() {
 				len(voiceStylePaths), len(textList))
 			os.Exit(1)
 		}
+		if len(langList) != len(textList) {
+			fmt.Printf("Error: Number of languages (%d) must match number of texts (%d)\n",
+				len(langList), len(textList))
+			os.Exit(1)
+		}
 	}
 
 	bsz := len(voiceStylePaths)
@@ -126,7 +142,7 @@ func main() {
 
 		if batch {
 			Timer("Generating speech from text", func() interface{} {
-				w, d, err := textToSpeech.Batch(textList, style, totalStep, speed)
+				w, d, err := textToSpeech.Batch(textList, langList, style, totalStep, speed)
 				if err != nil {
 					fmt.Printf("Error generating speech: %v\n", err)
 					os.Exit(1)
@@ -137,7 +153,7 @@ func main() {
 			})
 		} else {
 			Timer("Generating speech from text", func() interface{} {
-				w, d, err := textToSpeech.Call(textList[0], style, totalStep, speed, 0.3)
+				w, d, err := textToSpeech.Call(textList[0], langList[0], style, totalStep, speed, 0.3)
 				if err != nil {
 					fmt.Printf("Error generating speech: %v\n", err)
 					os.Exit(1)

go/go.mod

@@ -7,6 +7,7 @@ require (
 	github.com/go-audio/wav v1.1.0
 	github.com/mjibson/go-dsp v0.0.0-20180508042940-11479a337f12
 	github.com/yalue/onnxruntime_go v1.11.0
+	golang.org/x/text v0.14.0
 )
 
 require github.com/go-audio/riff v1.0.0 // indirect

go/go.sum

@@ -8,3 +8,5 @@ github.com/mjibson/go-dsp v0.0.0-20180508042940-11479a337f12 h1:dd7vnTDfjtwCETZD
 github.com/mjibson/go-dsp v0.0.0-20180508042940-11479a337f12/go.mod h1:i/KKcxEWEO8Yyl11DYafRPKOPVYTrhxiTRigjtEEXZU=
 github.com/yalue/onnxruntime_go v1.11.0 h1:aKH4yPIbqfcB3SfnQWq/WxzLelkyolntHnffL3eMBHY=
 github.com/yalue/onnxruntime_go v1.11.0/go.mod h1:b4X26A8pekNb1ACJ58wAXgNKeUCGEAQ9dmACut9Sm/4=
+golang.org/x/text v0.14.0 h1:ScX5w1eTa3QqT8oi6+ziP7dTV1S2+ALU0bI+0zXKWiQ=
+golang.org/x/text v0.14.0/go.mod h1:18ZOQIKpY8NJVqYksKHtTdi31H5itFRjB5/qKTNYzSU=

go/helper.go

@@ -10,12 +10,17 @@ import (
 	"regexp"
 	"strings"
 	"time"
+	"unicode"
 
 	"github.com/go-audio/audio"
 	"github.com/go-audio/wav"
 	ort "github.com/yalue/onnxruntime_go"
+	"golang.org/x/text/unicode/norm"
 )
 
+// Available languages for multilingual TTS
+var AvailableLangs = []string{"en", "ko", "es", "pt", "fr"}
+
 // Config structures
 type SpecProcessorConfig struct {
 	NFFT      int     `json:"n_fft"`
@@ -108,11 +113,11 @@ func NewUnicodeProcessor(unicodeIndexerPath string) (*UnicodeProcessor, error) {
 }
 
 // Call processes text list to text IDs and mask
-func (up *UnicodeProcessor) Call(textList []string) ([][]int64, [][][]float64) {
+func (up *UnicodeProcessor) Call(textList []string, langList []string) ([][]int64, [][][]float64) {
 	// Preprocess texts
 	processedTexts := make([]string, len(textList))
 	for i, text := range textList {
-		processedTexts[i] = preprocessText(text)
+		processedTexts[i] = preprocessText(text, langList[i])
 	}
 
 	// Get text lengths
@@ -325,14 +330,21 @@ func splitSentences(text string) []string {
 	return sentences
 }
 
-// Utility functions
+// isValidLang checks if a language is in the available languages list
-func preprocessText(text string) string {
+func isValidLang(lang string) bool {
-	// TODO: Need advanced normalizer for better performance
+	for _, l := range AvailableLangs {
-	// NOTE: Go doesn't have built-in NFKD normalization like Python
+		if l == lang {
-	// For full Unicode normalization, use golang.org/x/text/unicode/norm
+			return true
-	// This implementation handles basic text preprocessing
+		}
+	}
+	return false
+}
 
-	// FIXME: this should be fixed for non-English languages
+// Utility functions
+func preprocessText(text string, lang string) string {
+	// TODO: Need advanced normalizer for better performance
+	// Apply NFKD normalization using golang.org/x/text/unicode/norm
+	text = norm.NFKD.String(text)
 
 	// Remove emojis and various Unicode symbols
 	emojiPattern := regexp.MustCompile(`[\x{1F600}-\x{1F64F}\x{1F300}-\x{1F5FF}\x{1F680}-\x{1F6FF}\x{1F700}-\x{1F77F}\x{1F780}-\x{1F7FF}\x{1F800}-\x{1F8FF}\x{1F900}-\x{1F9FF}\x{1FA00}-\x{1FA6F}\x{1FA70}-\x{1FAFF}\x{2600}-\x{26FF}\x{2700}-\x{27BF}\x{1F1E6}-\x{1F1FF}]+`)
@@ -343,7 +355,6 @@ func preprocessText(text string) string {
 		"–": "-",    // en dash
 		"‑": "-",    // non-breaking hyphen
 		"—": "-",    // em dash
-		"¯": " ",    // macron
 		"_": " ",    // underscore
 		"\u201C": "\"",   // left double quote
 		"\u201D": "\"",   // right double quote
@@ -364,11 +375,6 @@ func preprocessText(text string) string {
 		text = strings.ReplaceAll(text, old, new)
 	}
 
-	// Remove combining diacritics (common combining marks)
-	// FIXME: this should be fixed for non-English languages
-	diacriticsPattern := regexp.MustCompile(`[\x{0302}\x{0303}\x{0304}\x{0305}\x{0306}\x{0307}\x{0308}\x{030A}\x{030B}\x{030C}\x{0327}\x{0328}\x{0329}\x{032A}\x{032B}\x{032C}\x{032D}\x{032E}\x{032F}]`)
-	text = diacriticsPattern.ReplaceAllString(text, "")
-
 	// Remove special symbols
 	specialSymbols := []string{"♥", "☆", "♡", "©", "\\"}
 	for _, symbol := range specialSymbols {
@@ -418,6 +424,14 @@ func preprocessText(text string) string {
 		}
 	}
 
+	// Validate language
+	if !isValidLang(lang) {
+		panic(fmt.Sprintf("Invalid language: %s. Available: %v", lang, AvailableLangs))
+	}
+
+	// Wrap text with language tags
+	text = fmt.Sprintf("<%s>%s</%s>", lang, text, lang)
+
 	return text
 }
 
@@ -661,11 +675,11 @@ func (tts *TextToSpeech) sampleNoisyLatent(durOnnx []float32) ([][][]float64, []
 	return noisyLatent, latentMask
 }
 
-func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
+func (tts *TextToSpeech) _infer(textList []string, langList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
 	bsz := len(textList)
 
 	// Process text
-	textIDs, textMask := tts.textProcessor.Call(textList)
+	textIDs, textMask := tts.textProcessor.Call(textList, langList)
 	textIDsShape := []int64{int64(bsz), int64(len(textIDs[0]))}
 	textMaskShape := []int64{int64(bsz), 1, int64(len(textMask[0][0]))}
 
@@ -785,14 +799,18 @@ func (tts *TextToSpeech) _infer(textList []string, style *Style, totalStep int,
 }
 
 // Call synthesizes speech from a single text with automatic chunking
-func (tts *TextToSpeech) Call(text string, style *Style, totalStep int, speed float32, silenceDuration float32) ([]float32, float32, error) {
+func (tts *TextToSpeech) Call(text string, lang string, style *Style, totalStep int, speed float32, silenceDuration float32) ([]float32, float32, error) {
-	chunks := chunkText(text, 0)
+	maxLen := 300
+	if lang == "ko" {
+		maxLen = 120
+	}
+	chunks := chunkText(text, maxLen)
 	
 	var wavCat []float32
 	var durCat float32
 
 	for i, chunk := range chunks {
-		wav, duration, err := tts._infer([]string{chunk}, style, totalStep, speed)
+		wav, duration, err := tts._infer([]string{chunk}, []string{lang}, style, totalStep, speed)
 		if err != nil {
 			return nil, 0, err
 		}
@@ -818,8 +836,8 @@ func (tts *TextToSpeech) Call(text string, style *Style, totalStep int, speed fl
 }
 
 // Batch synthesizes speech from multiple texts
-func (tts *TextToSpeech) Batch(textList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
+func (tts *TextToSpeech) Batch(textList []string, langList []string, style *Style, totalStep int, speed float32) ([]float32, []float32, error) {
-	return tts._infer(textList, style, totalStep, speed)
+	return tts._infer(textList, langList, style, totalStep, speed)
 }
 
 func (tts *TextToSpeech) Destroy() {
@@ -917,15 +935,17 @@ func InitializeONNXRuntime() error {
 	return nil
 }
 
-// sanitizeFilename creates a safe filename from text
+// sanitizeFilename creates a safe filename from text (supports Unicode)
 func sanitizeFilename(text string, maxLen int) string {
-	if len(text) > maxLen {
+	runes := []rune(text)
-		text = text[:maxLen]
+	if len(runes) > maxLen {
+		runes = runes[:maxLen]
 	}
 	
-	result := make([]rune, 0, len(text))
+	result := make([]rune, 0, len(runes))
-	for _, r := range text {
+	for _, r := range runes {
-		if (r >= 'a' && r <= 'z') || (r >= 'A' && r <= 'Z') || (r >= '0' && r <= '9') {
+		// unicode.IsLetter matches any Unicode letter, unicode.IsDigit matches any Unicode digit
+		if unicode.IsLetter(r) || unicode.IsDigit(r) {
 			result = append(result, r)
 		} else {
 			result = append(result, '_')

img/Supertonic_IMG_v02.svg

@@ -1,250 +0,0 @@
-<?xml version="1.0" encoding="UTF-8"?>
-<svg id="_레이어_2" data-name="레이어 2" xmlns="http://www.w3.org/2000/svg" xmlns:xlink="http://www.w3.org/1999/xlink" viewBox="0 0 1920 1080">
-  <defs>
-    <style>
-      .cls-1, .cls-2 {
-        fill: none;
-      }
-
-      .cls-3 {
-        fill: #227cff;
-      }
-
-      .cls-4 {
-        fill: #ff0;
-      }
-
-      .cls-2 {
-        stroke: #0a0a0a;
-        stroke-miterlimit: 10;
-        stroke-width: 1.72px;
-      }
-
-      .cls-5 {
-        fill: #f2f2f2;
-      }
-
-      .cls-6 {
-        fill: #0a0a0a;
-      }
-
-      .cls-7 {
-        clip-path: url(#clippath);
-      }
-    </style>
-    <clipPath id="clippath">
-      <rect class="cls-1" x="181.43" width="1626.55" height="1080"/>
-    </clipPath>
-  </defs>
-  <g id="Work">
-    <g>
-      <rect class="cls-5" width="1920" height="1080"/>
-      <g>
-        <circle class="cls-3" cx="1679.4" cy="880.43" r="59.81"/>
-        <path class="cls-6" d="M1713.35,805.14c-5.14,12.55-10.93,23.87-18.55,37.52l14.39-2.21c-12.75,23.11-27.5,45.05-44.09,65.57l14.46-2.22c-18.8,23.34-39.84,44.76-62.85,63.95,37.17-24.18,63.26-49.33,92.3-75.66l-16.71,2.56c24.03-21.85,46.85-44.98,68.39-69.3l-22.1,3.39c10.89-12.33,20.91-24.28,30.11-35.66l-55.34,12.05Z"/>
-      </g>
-      <g class="cls-7">
-        <path class="cls-4" d="M1036.15-20.65c-38.28,93.45-81.37,177.77-138.14,279.42l107.16-16.43c-94.95,172.09-204.79,335.46-328.29,488.29l107.68-16.51c-139.96,173.79-296.71,333.29-468.05,476.23,276.77-180.08,471.07-367.33,687.29-563.39l-124.4,19.07c178.91-162.71,348.9-334.99,509.26-516.04l-164.57,25.23c81.12-91.85,155.67-180.81,224.18-265.57l-412.13,89.69Z"/>
-      </g>
-      <g>
-        <path class="cls-6" d="M157.78,462.19h7.78v52.03h28.69v7.36h-36.47v-59.39Z"/>
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ios/ExampleiOSApp/ContentView.swift

@@ -12,7 +12,7 @@ struct ContentView: View {
                 Spacer()
 
                 VStack(spacing: 12) {
-                    Text("SupertonicTTS iOS Demo")
+                    Text("Supertonic 2 iOS Demo")
                         .font(.title2.weight(.semibold))
                         .foregroundColor(.primary)
 
@@ -44,6 +44,19 @@ struct ContentView: View {
                     }
                     .pickerStyle(SegmentedPickerStyle())
                     .padding(.horizontal)
+                    
+                    HStack(spacing: 12) {
+                        Text("Language")
+                            .font(.subheadline)
+                            .foregroundColor(.secondary)
+                        Picker("Language", selection: $vm.language) {
+                            ForEach(TTSService.Language.allCases, id: \.self) { lang in
+                                Text(lang.displayName).tag(lang)
+                            }
+                        }
+                        .pickerStyle(MenuPickerStyle())
+                    }
+                    .padding(.horizontal)
                 }
 
                 HStack(spacing: 16) {

ios/ExampleiOSApp/TTSService.swift

@@ -3,6 +3,23 @@ import OnnxRuntimeBindings
 
 final class TTSService {
     enum Voice { case male, female }
+    enum Language: String, CaseIterable {
+        case en = "en"
+        case ko = "ko"
+        case es = "es"
+        case pt = "pt"
+        case fr = "fr"
+        
+        var displayName: String {
+            switch self {
+            case .en: return "English"
+            case .ko: return "한국어"
+            case .es: return "Español"
+            case .pt: return "Português"
+            case .fr: return "Français"
+            }
+        }
+    }
 
     private let env: ORTEnv
     private let textToSpeech: TextToSpeech
@@ -16,13 +33,13 @@ final class TTSService {
         sampleRate = textToSpeech.sampleRate
     }
 
-    func synthesize(text: String, nfe: Int, voice: Voice) async throws -> URL {
+    func synthesize(text: String, nfe: Int, voice: Voice, language: Language) async throws -> URL {
         // Load style for the selected voice
         let styleURL = try Self.locateVoiceStyleURL(voice: voice)
         let style = try loadVoiceStyle([styleURL.path], verbose: false)
 
         // 2) Synthesize via packed TextToSpeech component
-        let (wav, duration) = try textToSpeech.call(text, style, nfe)
+        let (wav, duration) = try textToSpeech.call(text, language.rawValue, style, nfe)
         let audioSeconds = Double(duration)
         let wavLenSample = min(Int(Double(sampleRate) * audioSeconds), wav.count)
         let wavOut = Array(wav[0..<wavLenSample])

ios/ExampleiOSApp/TTSViewModel.swift

@@ -6,6 +6,7 @@ final class TTSViewModel: ObservableObject {
     @Published var text: String = "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."
     @Published var nfe: Double = 5
     @Published var voice: TTSService.Voice = .male
+    @Published var language: TTSService.Language = .en
     @Published var isGenerating: Bool = false
     @Published var isPlaying: Bool = false
     @Published var errorMessage: String?
@@ -39,7 +40,7 @@ final class TTSViewModel: ObservableObject {
         Task {
             let tic = Date()
             do {
-                let url = try await service.synthesize(text: text, nfe: Int(nfe), voice: voice)
+                let url = try await service.synthesize(text: text, nfe: Int(nfe), voice: voice, language: language)
                 let elapsed = Date().timeIntervalSince(tic)
                 let audio = audioDuration(at: url)
                 await MainActor.run {

ios/README.md

@@ -1,14 +1,23 @@
 # Supertonic iOS Example App
 
-A minimal iOS demo that runs Supertonic (ONNX Runtime) on-device. The app shows:
+A minimal iOS demo that runs Supertonic 2 (ONNX Runtime) on-device. The app shows:
 - Multiline text input
 - NFE (denoising steps) slider
 - Voice toggle (M/F)
+- Language selector (en, ko, es, pt, fr)
 - Generate & Play buttons
 - RTF display (Elapsed / Audio seconds)
 
 All ONNX models/configs are reused from `Supertonic/assets/onnx`, and voice style JSON files from `Supertonic/assets/voice_styles`.
 
+## 📰 Update News
+
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 ## Prerequisites
 - macOS 13+, Xcode 15+
 - Swift 5.9+
@@ -53,7 +62,17 @@ These references are defined in `project.yml` and added to the app bundle by Xco
 ## App Controls
 - **Text**: Multiline `TextEditor`
 - **NFE**: Denoising steps (default 5)
-- **Voice**: M1/M2/F1/F2 voice style selector (4 pre-extracted styles)
+- **Voice**: M/F voice style selector
+- **Language**: Language selector (English, 한국어, Español, Português, Français)
 - **Generate**: Runs end-to-end synthesis
 - **Play/Stop**: Controls playback of the last output
-- **RTF**: Shows Elapsed / Audio seconds for quick performance intuition
+- **RTF**: Shows Elapsed / Audio seconds for quick performance intuition
+
+## Multilingual Support
+
+Supertonic 2 supports multiple languages. Select the appropriate language for your input text:
+- **English (en)**: Default language
+- **한국어 (ko)**: Korean
+- **Español (es)**: Spanish
+- **Português (pt)**: Portuguese
+- **Français (fr)**: French

java/ExampleONNX.java

@@ -21,6 +21,7 @@ public class ExampleONNX {
         List<String> text = Arrays.asList(
             "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."
         );
+        List<String> lang = Arrays.asList("en");
         String saveDir = "results";
         boolean batch = false;
     }
@@ -58,6 +59,11 @@ public class ExampleONNX {
                         result.text = Arrays.asList(args[++i].split("\\|"));
                     }
                     break;
+                case "--lang":
+                    if (i + 1 < args.length) {
+                        result.lang = Arrays.asList(args[++i].split(","));
+                    }
+                    break;
                 case "--save-dir":
                     if (i + 1 < args.length) result.saveDir = args[++i];
                     break;
@@ -85,6 +91,7 @@ public class ExampleONNX {
             String saveDir = parsedArgs.saveDir;
             List<String> voiceStylePaths = parsedArgs.voiceStyle;
             List<String> textList = parsedArgs.text;
+            List<String> langList = parsedArgs.lang;
             boolean batch = parsedArgs.batch;
             
             if (batch) {
@@ -92,6 +99,10 @@ public class ExampleONNX {
                     throw new RuntimeException("Number of voice styles (" + voiceStylePaths.size() + 
                         ") must match number of texts (" + textList.size() + ")");
                 }
+                if (langList.size() != textList.size()) {
+                    throw new RuntimeException("Number of languages (" + langList.size() + 
+                        ") must match number of texts (" + textList.size() + ")");
+                }
             }
             
             int bsz = voiceStylePaths.size();
@@ -116,7 +127,7 @@ public class ExampleONNX {
                 if (batch) {
                     ttsResult = Helper.timer("Generating speech from text", () -> {
                         try {
-                            return textToSpeech.batch(textList, style, totalStep, speed, env);
+                            return textToSpeech.batch(textList, langList, style, totalStep, speed, env);
                         } catch (Exception e) {
                             throw new RuntimeException(e);
                         }
@@ -124,7 +135,7 @@ public class ExampleONNX {
                 } else {
                     ttsResult = Helper.timer("Generating speech from text", () -> {
                         try {
-                            return textToSpeech.call(textList.get(0), style, totalStep, speed, 0.3f, env);
+                            return textToSpeech.call(textList.get(0), langList.get(0), style, totalStep, speed, 0.3f, env);
                         } catch (Exception e) {
                             throw new RuntimeException(e);
                         }

java/Helper.java

@@ -18,6 +18,17 @@ import java.util.*;
 import java.util.regex.Pattern;
 import java.util.regex.Matcher;
 
+/**
+ * Available languages for multilingual TTS
+ */
+class Languages {
+    public static final List<String> AVAILABLE = Arrays.asList("en", "ko", "es", "pt", "fr");
+    
+    public static boolean isValid(String lang) {
+        return AVAILABLE.contains(lang);
+    }
+}
+
 /**
  * Configuration classes
  */
@@ -96,22 +107,28 @@ class UnicodeProcessor {
         return result.toString();
     }
     
-    public TextProcessResult call(List<String> textList) {
+    public TextProcessResult call(List<String> textList, List<String> langList) {
         List<String> processedTexts = new ArrayList<>();
-        for (String text : textList) {
+        for (int i = 0; i < textList.size(); i++) {
-            processedTexts.add(preprocessText(text));
+            processedTexts.add(preprocessText(textList.get(i), langList.get(i)));
+        }
+        
+        // Convert texts to unicode values first to get correct character counts
+        List<int[]> allUnicodeVals = new ArrayList<>();
+        for (String text : processedTexts) {
+            allUnicodeVals.add(textToUnicodeValues(text));
         }
         
         int[] textIdsLengths = new int[processedTexts.size()];
         int maxLen = 0;
-        for (int i = 0; i < processedTexts.size(); i++) {
+        for (int i = 0; i < allUnicodeVals.size(); i++) {
-            textIdsLengths[i] = processedTexts.get(i).length();
+            textIdsLengths[i] = allUnicodeVals.get(i).length;  // Use code point count, not char count
             maxLen = Math.max(maxLen, textIdsLengths[i]);
         }
         
         long[][] textIds = new long[processedTexts.size()][maxLen];
-        for (int i = 0; i < processedTexts.size(); i++) {
+        for (int i = 0; i < allUnicodeVals.size(); i++) {
-            int[] unicodeVals = textToUnicodeValues(processedTexts.get(i));
+            int[] unicodeVals = allUnicodeVals.get(i);
             for (int j = 0; j < unicodeVals.length; j++) {
                 textIds[i][j] = indexer[unicodeVals[j]];
             }
@@ -121,12 +138,10 @@ class UnicodeProcessor {
         return new TextProcessResult(textIds, textMask);
     }
     
-    private String preprocessText(String text) {
+    private String preprocessText(String text, String lang) {
         // TODO: Need advanced normalizer for better performance
         text = Normalizer.normalize(text, Normalizer.Form.NFKD);
 
-        // FIXME: this should be fixed for non-English languages
-
         // Remove emojis (wide Unicode range)
         // Java Pattern doesn't support \x{...} syntax for Unicode above \uFFFF
         // Use character filtering instead
@@ -137,7 +152,6 @@ class UnicodeProcessor {
         replacements.put("–", "-");      // en dash
         replacements.put("‑", "-");      // non-breaking hyphen
         replacements.put("—", "-");      // em dash
-        replacements.put("¯", " ");      // macron
         replacements.put("_", " ");      // underscore
         replacements.put("\u201C", "\"");     // left double quote
         replacements.put("\u201D", "\"");     // right double quote
@@ -157,9 +171,6 @@ class UnicodeProcessor {
             text = text.replace(entry.getKey(), entry.getValue());
         }
 
-        // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-        text = text.replaceAll("[\\u0302\\u0303\\u0304\\u0305\\u0306\\u0307\\u0308\\u030A\\u030B\\u030C\\u0327\\u0328\\u0329\\u032A\\u032B\\u032C\\u032D\\u032E\\u032F]", "");
-
         // Remove special symbols
         text = text.replaceAll("[♥☆♡©\\\\]", "");
 
@@ -201,15 +212,20 @@ class UnicodeProcessor {
             text += ".";
         }
 
+        // Validate language
+        if (!Languages.isValid(lang)) {
+            throw new IllegalArgumentException("Invalid language: " + lang + ". Available: " + Languages.AVAILABLE);
+        }
+
+        // Wrap text with language tags
+        text = "<" + lang + ">" + text + "</" + lang + ">";
+
         return text;
     }
     
     private int[] textToUnicodeValues(String text) {
-        int[] values = new int[text.length()];
+        // Use codePoints() stream to correctly handle surrogate pairs
-        for (int i = 0; i < text.length(); i++) {
+        return text.codePoints().toArray();
-            values[i] = text.codePointAt(i);
-        }
-        return values;
     }
     
     private float[][][] getTextMask(int[] lengths) {
@@ -269,12 +285,12 @@ class TextToSpeech {
         this.ldim = config.ttl.latentDim;
     }
     
-    private TTSResult _infer(List<String> textList, Style style, int totalStep, float speed, OrtEnvironment env) 
+    private TTSResult _infer(List<String> textList, List<String> langList, Style style, int totalStep, float speed, OrtEnvironment env) 
             throws OrtException {
         int bsz = textList.size();
         
         // Process text
-        UnicodeProcessor.TextProcessResult textResult = textProcessor.call(textList);
+        UnicodeProcessor.TextProcessResult textResult = textProcessor.call(textList, langList);
         long[][] textIds = textResult.textIds;
         float[][][] textMask = textResult.textMask;
         
@@ -360,7 +376,18 @@ class TextToSpeech {
         
         OrtSession.Result vocoderResult = vocoderSession.run(vocoderInputs);
         float[][] wavBatch = (float[][]) vocoderResult.get(0).getValue();
-        float[] wav = wavBatch[0];
+        
+        // Flatten all batch audio into a single array for batch processing
+        int totalSamples = 0;
+        for (float[] w : wavBatch) {
+            totalSamples += w.length;
+        }
+        float[] wav = new float[totalSamples];
+        int offset = 0;
+        for (float[] w : wavBatch) {
+            System.arraycopy(w, 0, wav, offset, w.length);
+            offset += w.length;
+        }
         
         // Clean up
         textIdsTensor.close();
@@ -421,15 +448,16 @@ class TextToSpeech {
     /**
      * Synthesize speech from a single text with automatic chunking
      */
-    public TTSResult call(String text, Style style, int totalStep, float speed, float silenceDuration, OrtEnvironment env) 
+    public TTSResult call(String text, String lang, Style style, int totalStep, float speed, float silenceDuration, OrtEnvironment env) 
             throws OrtException {
-        List<String> chunks = Helper.chunkText(text, 0);
+        int maxLen = lang.equals("ko") ? 120 : 300;
+        List<String> chunks = Helper.chunkText(text, maxLen);
         
         List<Float> wavCat = new ArrayList<>();
         float durCat = 0.0f;
         
         for (int i = 0; i < chunks.size(); i++) {
-            TTSResult result = _infer(Arrays.asList(chunks.get(i)), style, totalStep, speed, env);
+            TTSResult result = _infer(Arrays.asList(chunks.get(i)), Arrays.asList(lang), style, totalStep, speed, env);
             
             float dur = result.duration[0];
             int wavLen = (int) (sampleRate * dur);
@@ -464,9 +492,9 @@ class TextToSpeech {
     /**
      * Batch synthesize speech from multiple texts
      */
-    public TTSResult batch(List<String> textList, Style style, int totalStep, float speed, OrtEnvironment env) 
+    public TTSResult batch(List<String> textList, List<String> langList, Style style, int totalStep, float speed, OrtEnvironment env) 
             throws OrtException {
-        return _infer(textList, style, totalStep, speed, env);
+        return _infer(textList, langList, style, totalStep, speed, env);
     }
     
     public void close() throws OrtException {
@@ -841,13 +869,20 @@ public class Helper {
     }
     
     /**
-     * Sanitize filename
+     * Sanitize filename (supports Unicode characters)
      */
     public static String sanitizeFilename(String text, int maxLen) {
-        if (text.length() > maxLen) {
+        // Get first maxLen characters (code points, not chars for surrogate pairs)
-            text = text.substring(0, maxLen);
+        int[] codePoints = text.codePoints().limit(maxLen).toArray();
+        StringBuilder result = new StringBuilder();
+        for (int codePoint : codePoints) {
+            if (Character.isLetterOrDigit(codePoint)) {
+                result.appendCodePoint(codePoint);
+            } else {
+                result.append('_');
+            }
         }
-        return text.replaceAll("[^a-zA-Z0-9]", "_");
+        return result.toString();
     }
     
     /**

java/README.md

@@ -4,6 +4,12 @@ This guide provides examples for running TTS inference using `ExampleONNX.java`.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -43,13 +49,13 @@ This will use:
 ### Example 2: Batch Inference
 Process multiple voice styles and texts at once:
 ```bash
-mvn exec:java -Dexec.args="--batch --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json --text 'The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant.'"
+mvn exec:java -Dexec.args="--batch --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json --text 'The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요.' --lang en,ko"
 ```
 
 This will:
-- Generate speech for 2 different voice-text pairs
+- Generate speech for 2 different voice-text-language pairs
-- Use male voice (M1.json) for the first text
+- Use male voice (M1.json) for the first text in English
-- Use female voice (F1.json) for the second text
+- Use female voice (F1.json) for the second text in Korean
 - Process both samples in a single batch
 
 ### Example 3: High Quality Inference
@@ -107,14 +113,16 @@ java -jar target/tts-example.jar --total-step 10 --text "Your custom text here"
 | `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
-| `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
+| `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s), comma-separated |
-| `--text` | str+ | (long default text) | Text(s) to synthesize |
+| `--text` | str+ | (long default text) | Text(s) to synthesize, pipe-separated |
+| `--lang` | str+ | `en` | Language(s) for synthesis, comma-separated (en, ko, es, pt, fr) |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (multiple text-style pairs, disables automatic chunking) |
 
 ## Notes
 
-- **Batch Processing**: When using `--batch`, the number of `--voice-style` files must match the number of `--text` entries
+- **Multilingual Support**: Use `--lang` to specify the language for each text. Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
+- **Batch Processing**: When using `--batch`, the number of `--voice-style`, `--text`, and `--lang` entries must match
 - **Automatic Chunking**: Without `--batch`, long texts are automatically split and concatenated with 0.3s pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

nodejs/README.md

@@ -4,6 +4,12 @@ Node.js implementation for TTS inference. Uses ONNX Runtime to generate speech f
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -47,15 +53,16 @@ Process multiple voice styles and texts at once:
 ```bash
 node example_onnx.js \
   --voice-style "assets/voice_styles/M1.json,assets/voice_styles/F1.json" \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant." \
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 좋아서 한참을 멈춰 서서 들었어요." \
+  --lang "en,ko" \
   --batch
 ```
 
 This will:
 - Use `--batch` flag to enable batch processing mode
 - Generate speech for 2 different voice-text pairs
-- Use male voice style (M1.json) for the first text
+- Use male voice style (M1.json) for the first English text
-- Use female voice style (F1.json) for the second text
+- Use female voice style (F1.json) for the second Korean text
 - Process both samples in a single batch (automatic text chunking disabled)
 
 ### Example 3: High Quality Inference
@@ -94,15 +101,18 @@ This will:
 | `--use-gpu` | flag | False | Use GPU for inference (not supported yet) |
 | `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
+| `--speed` | float | 1.05 | Speech speed factor (higher = faster, lower = slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s). Separate multiple files with commas |
 | `--text` | str+ | (long default text) | Text(s) to synthesize. Separate multiple texts with pipes |
+| `--lang` | str+ | `en` | Language(s) for text(s): `en`, `ko`, `es`, `pt`, `fr`. Separate multiple with commas |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (disables automatic text chunking) |
 
 ## Notes
 
 - **Batch Processing**: The number of voice style files must match the number of texts. Use commas to separate files and pipes to separate texts
+- **Multilingual Support**: Use `--lang` to specify language(s). Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
 - **Long-Form Inference**: Without `--batch` flag, long texts are automatically chunked and combined into a single audio file with natural pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

nodejs/example_onnx.js

@@ -2,7 +2,7 @@ import fs from 'fs';
 import path from 'path';
 import { fileURLToPath } from 'url';
 
-import { loadTextToSpeech, loadVoiceStyle, timer, writeWavFile } from './helper.js';
+import { loadTextToSpeech, loadVoiceStyle, timer, writeWavFile, sanitizeFilename } from './helper.js';
 
 const __filename = fileURLToPath(import.meta.url);
 const __dirname = path.dirname(__filename);
@@ -19,6 +19,7 @@ function parseArgs() {
         nTest: 4,
         voiceStyle: ['assets/voice_styles/M1.json'],
         text: ['This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen.'],
+        lang: ['en'],
         saveDir: 'results',
         batch: false
     };
@@ -41,6 +42,8 @@ function parseArgs() {
             args.voiceStyle = process.argv[++i].split(',');
         } else if (arg === '--text' && i + 1 < process.argv.length) {
             args.text = process.argv[++i].split('|');
+        } else if (arg === '--lang' && i + 1 < process.argv.length) {
+            args.lang = process.argv[++i].split(',');
         } else if (arg === '--save-dir' && i + 1 < process.argv.length) {
             args.saveDir = process.argv[++i];
         }
@@ -63,6 +66,7 @@ async function main() {
     const saveDir = args.saveDir;
     const voiceStylePaths = args.voiceStyle.map(p => path.resolve(__dirname, p));
     const textList = args.text;
+    const langList = args.lang;
     const batch = args.batch;
 
     if (voiceStylePaths.length !== textList.length) {
@@ -83,9 +87,9 @@ async function main() {
         
         const { wav, duration } = await timer('Generating speech from text', async () => {
             if (batch) {
-                return await textToSpeech.batch(textList, style, totalStep, speed);
+                return await textToSpeech.batch(textList, langList, style, totalStep, speed);
             } else {
-                return await textToSpeech.call(textList[0], style, totalStep, speed);
+                return await textToSpeech.call(textList[0], langList[0], style, totalStep, speed);
             }
         });
         
@@ -95,7 +99,7 @@ async function main() {
 
         const wavShape = [bsz, wav.length / bsz];
         for (let b = 0; b < bsz; b++) {
-            const fname = `${textList[b].substring(0, 20).replace(/[^a-zA-Z0-9]/g, '_')}_${n + 1}.wav`;
+            const fname = `${sanitizeFilename(textList[b], 20)}_${n + 1}.wav`;
             const wavLen = Math.floor(textToSpeech.sampleRate * duration[b]);
             const wavOut = wav.slice(b * wavShape[1], b * wavShape[1] + wavLen);
             

nodejs/helper.js

@@ -5,6 +5,8 @@ import * as ort from 'onnxruntime-node';
 
 const __filename = fileURLToPath(import.meta.url);
 
+const AVAILABLE_LANGS = ["en", "ko", "es", "pt", "fr"];
+
 /**
  * Unicode text processor
  */
@@ -13,12 +15,10 @@ class UnicodeProcessor {
         this.indexer = JSON.parse(fs.readFileSync(unicodeIndexerJsonPath, 'utf8'));
     }
 
-    _preprocessText(text) {
+    _preprocessText(text, lang) {
         // TODO: Need advanced normalizer for better performance
         text = text.normalize('NFKD');
 
-        // FIXME: this should be fixed for non-English languages
-
         // Remove emojis (wide Unicode range)
         const emojiPattern = /[\u{1F600}-\u{1F64F}\u{1F300}-\u{1F5FF}\u{1F680}-\u{1F6FF}\u{1F700}-\u{1F77F}\u{1F780}-\u{1F7FF}\u{1F800}-\u{1F8FF}\u{1F900}-\u{1F9FF}\u{1FA00}-\u{1FA6F}\u{1FA70}-\u{1FAFF}\u{2600}-\u{26FF}\u{2700}-\u{27BF}\u{1F1E6}-\u{1F1FF}]+/gu;
         text = text.replace(emojiPattern, '');
@@ -28,12 +28,11 @@ class UnicodeProcessor {
             '–': '-',
             '‑': '-',
             '—': '-',
-            '¯': ' ',
             '_': ' ',
-            '"': '"',
+            '\u201C': '"',  // left double quote "
-            '"': '"',
+            '\u201D': '"',  // right double quote "
-            '\u2018': "'",  // left single quote
+            '\u2018': "'",  // left single quote '
-            '\u2019': "'",  // right single quote
+            '\u2019': "'",  // right single quote '
             '´': "'",
             '`': "'",
             '[': ' ',
@@ -48,9 +47,6 @@ class UnicodeProcessor {
             text = text.replaceAll(k, v);
         }
 
-        // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-        text = text.replace(/[\u0302\u0303\u0304\u0305\u0306\u0307\u0308\u030A\u030B\u030C\u0327\u0328\u0329\u032A\u032B\u032C\u032D\u032E\u032F]/g, '');
-
         // Remove special symbols
         text = text.replace(/[♥☆♡©\\]/g, '');
 
@@ -92,6 +88,14 @@ class UnicodeProcessor {
             text += '.';
         }
 
+        // Validate language
+        if (!AVAILABLE_LANGS.includes(lang)) {
+            throw new Error(`Invalid language: ${lang}. Available: ${AVAILABLE_LANGS.join(', ')}`);
+        }
+        
+        // Wrap text with language tags
+        text = `<${lang}>` + text + `</${lang}>`;
+
         return text;
     }
 
@@ -103,8 +107,8 @@ class UnicodeProcessor {
         return lengthToMask(textIdsLengths);
     }
 
-    call(textList) {
+    call(textList, langList) {
-        const processedTexts = textList.map(t => this._preprocessText(t));
+        const processedTexts = textList.map((t, i) => this._preprocessText(t, langList[i]));
         const textIdsLengths = processedTexts.map(t => t.length);
         const maxLen = Math.max(...textIdsLengths);
         
@@ -191,12 +195,12 @@ class TextToSpeech {
         return { noisyLatent, latentMask };
     }
 
-    async _infer(textList, style, totalStep, speed = 1.05) {
+    async _infer(textList, langList, style, totalStep, speed = 1.05) {
         if (textList.length !== style.ttl.dims[0]) {
             throw new Error('Number of texts must match number of style vectors');
         }
         const bsz = textList.length;
-        const { textIds, textMask } = this.textProcessor.call(textList);
+        const { textIds, textMask } = this.textProcessor.call(textList, langList);
         const textIdsShape = [bsz, textIds[0].length];
         const textMaskShape = [bsz, 1, textMask[0][0].length];
         
@@ -267,16 +271,17 @@ class TextToSpeech {
         return { wav, duration: durOnnx };
     }
 
-    async call(text, style, totalStep, speed = 1.05, silenceDuration = 0.3) {
+    async call(text, lang, style, totalStep, speed = 1.05, silenceDuration = 0.3) {
         if (style.ttl.dims[0] !== 1) {
             throw new Error('Single speaker text to speech only supports single style');
         }
-        const textList = chunkText(text);
+        const maxLen = lang === 'ko' ? 120 : 300;
+        const textList = chunkText(text, maxLen);
         let wavCat = null;
         let durCat = 0;
         
         for (const chunk of textList) {
-            const { wav, duration } = await this._infer([chunk], style, totalStep, speed);
+            const { wav, duration } = await this._infer([chunk], [lang], style, totalStep, speed);
             
             if (wavCat === null) {
                 wavCat = wav;
@@ -292,8 +297,8 @@ class TextToSpeech {
         return { wav: wavCat, duration: [durCat] };
     }
 
-    async batch(textList, style, totalStep, speed = 1.05) {
+    async batch(textList, langList, style, totalStep, speed = 1.05) {
-        return await this._infer(textList, style, totalStep, speed);
+        return await this._infer(textList, langList, style, totalStep, speed);
     }
 }
 
@@ -502,6 +507,15 @@ export async function timer(name, fn) {
     return result;
 }
 
+/**
+ * Sanitize filename by replacing non-alphanumeric characters with underscores (supports Unicode)
+ */
+export function sanitizeFilename(text, maxLen) {
+    const prefix = text.substring(0, maxLen);
+    // \p{L} matches any Unicode letter, \p{N} matches any Unicode number
+    return prefix.replace(/[^\p{L}\p{N}_]/gu, '_');
+}
+
 /**
  * Chunk text into manageable segments
  */

py/README.md

@@ -4,6 +4,14 @@ This guide provides examples for running TTS inference using `example_onnx.py`.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added `supertonic` PyPI package! Install via `pip install supertonic` for a streamlined experience. This is a separate usage method from the ONNX examples in this directory. For more details, visit [supertonic-py documentation](https://supertone-inc.github.io/supertonic-py) and see `example_pypi.py` for usage.
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed. Adjust the speed factor to make speech faster or slower while maintaining natural quality.
@@ -49,15 +57,16 @@ Process multiple voice styles and texts at once:
 ```bash
 uv run example_onnx.py \
   --voice-style assets/voice_styles/M1.json assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange." "The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant." \
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange." "오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 좋아서 한참을 멈춰 서서 들었어요." \
+  --lang en ko \
   --batch
 ```
 
 This will:
 - Use `--batch` flag to enable batch processing mode
 - Generate speech for 2 different voice-text pairs
-- Use male voice style (M1.json) for the first text
+- Use male voice style (M1.json) for the first English text
-- Use female voice style (F1.json) for the second text
+- Use female voice style (F1.json) for the second Korean text
 - Process both samples in a single batch (automatic text chunking disabled)
 
 ### Example 3: High Quality Inference
@@ -122,12 +131,14 @@ This will:
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
 | `--text` | str+ | (long default text) | Text(s) to synthesize |
+| `--lang` | str+ | `en` | Language(s) for text(s): `en`, `ko`, `es`, `pt`, `fr` |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (disables automatic text chunking) |
 
 ## Notes
 
 - **Batch Processing**: The number of `--voice-style` files must match the number of `--text` entries
+- **Multilingual Support**: Use `--lang` to specify language(s). Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
 - **Long-Form Inference**: Without `--batch` flag, long texts are automatically chunked and combined into a single audio file with natural pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

py/example_onnx.py

@@ -56,6 +56,13 @@ def parse_args():
         ],
         help="Text(s) to synthesize. Can specify multiple texts for batch processing",
     )
+    parser.add_argument(
+        "--lang",
+        type=str,
+        nargs="+",
+        default=["en"],
+        help="Language(s) of the text(s). Can specify multiple languages for batch processing",
+    )
     parser.add_argument(
         "--save-dir", type=str, default="results", help="Output directory"
     )
@@ -73,6 +80,7 @@ n_test = args.n_test
 save_dir = args.save_dir
 voice_style_paths = args.voice_style
 text_list = args.text
+lang_list = args.lang
 batch = args.batch
 
 assert len(voice_style_paths) == len(
@@ -91,9 +99,13 @@ for n in range(n_test):
     print(f"\n[{n+1}/{n_test}] Starting synthesis...")
     with timer("Generating speech from text"):
         if batch:
-            wav, duration = text_to_speech.batch(text_list, style, total_step, speed)
+            wav, duration = text_to_speech.batch(
+                text_list, lang_list, style, total_step, speed
+            )
         else:
-            wav, duration = text_to_speech(text_list[0], style, total_step, speed)
+            wav, duration = text_to_speech(
+                text_list[0], lang_list[0], style, total_step, speed
+            )
     if not os.path.exists(save_dir):
         os.makedirs(save_dir)
     for b in range(bsz):

py/example_pypi.py

@@ -0,0 +1,16 @@
+from supertonic import TTS
+
+# Note: First run downloads model automatically (~260MB)
+tts = TTS(auto_download=True)
+
+# Get a voice style
+style = tts.get_voice_style(voice_name="M4")
+
+# Generate speech
+text = "This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."
+wav, duration = tts.synthesize(text, voice_style=style)
+# wav: np.ndarray, shape = (1, num_samples)
+# duration: np.ndarray, shape = (1,)
+
+# Save to file
+tts.save_audio(wav, "results/example_pypi.wav")

py/helper.py

@@ -10,18 +10,18 @@ import onnxruntime as ort
 
 import re
 
+AVAILABLE_LANGS = ["en", "ko", "es", "pt", "fr"]
+
 
 class UnicodeProcessor:
     def __init__(self, unicode_indexer_path: str):
         with open(unicode_indexer_path, "r") as f:
             self.indexer = json.load(f)
 
-    def _preprocess_text(self, text: str) -> str:
+    def _preprocess_text(self, text: str, lang: str) -> str:
         # TODO: Need advanced normalizer for better performance
         text = normalize("NFKD", text)
 
-        # FIXME: this should be fixed for non-English languages
-
         # Remove emojis (wide Unicode range)
         emoji_pattern = re.compile(
             "[\U0001f600-\U0001f64f"  # emoticons
@@ -45,12 +45,11 @@ class UnicodeProcessor:
             "–": "-",
             "‑": "-",
             "—": "-",
-            "¯": " ",
             "_": " ",
-            "“": '"',
+            "\u201c": '"',  # left double quote "
-            "”": '"',
+            "\u201d": '"',  # right double quote "
-            "‘": "'",
+            "\u2018": "'",  # left single quote '
-            "’": "'",
+            "\u2019": "'",  # right single quote '
             "´": "'",
             "`": "'",
             "[": " ",
@@ -64,13 +63,6 @@ class UnicodeProcessor:
         for k, v in replacements.items():
             text = text.replace(k, v)
 
-        # Remove combining diacritics # FIXME: this should be fixed for non-English languages
-        text = re.sub(
-            r"[\u0302\u0303\u0304\u0305\u0306\u0307\u0308\u030A\u030B\u030C\u0327\u0328\u0329\u032A\u032B\u032C\u032D\u032E\u032F]",
-            "",
-            text,
-        )
-
         # Remove special symbols
         text = re.sub(r"[♥☆♡©\\]", "", text)
 
@@ -107,6 +99,9 @@ class UnicodeProcessor:
         if not re.search(r"[.!?;:,'\"')\]}…。」』】〉》›»]$", text):
             text += "."
 
+        if lang not in AVAILABLE_LANGS:
+            raise ValueError(f"Invalid language: {lang}")
+        text = f"<{lang}>" + text + f"</{lang}>"
         return text
 
     def _get_text_mask(self, text_ids_lengths: np.ndarray) -> np.ndarray:
@@ -119,8 +114,12 @@ class UnicodeProcessor:
         )  # 2 bytes
         return unicode_values
 
-    def __call__(self, text_list: list[str]) -> tuple[np.ndarray, np.ndarray]:
+    def __call__(
-        text_list = [self._preprocess_text(t) for t in text_list]
+        self, text_list: list[str], lang_list: list[str]
+    ) -> tuple[np.ndarray, np.ndarray]:
+        text_list = [
+            self._preprocess_text(t, lang) for t, lang in zip(text_list, lang_list)
+        ]
         text_ids_lengths = np.array([len(text) for text in text_list], dtype=np.int64)
         text_ids = np.zeros((len(text_list), text_ids_lengths.max()), dtype=np.int64)
         for i, text in enumerate(text_list):
@@ -176,13 +175,18 @@ class TextToSpeech:
         return noisy_latent, latent_mask
 
     def _infer(
-        self, text_list: list[str], style: Style, total_step: int, speed: float = 1.05
+        self,
+        text_list: list[str],
+        lang_list: list[str],
+        style: Style,
+        total_step: int,
+        speed: float = 1.05,
     ) -> tuple[np.ndarray, np.ndarray]:
         assert (
             len(text_list) == style.ttl.shape[0]
         ), "Number of texts must match number of style vectors"
         bsz = len(text_list)
-        text_ids, text_mask = self.text_processor(text_list)
+        text_ids, text_mask = self.text_processor(text_list, lang_list)
         dur_onnx, *_ = self.dp_ort.run(
             None, {"text_ids": text_ids, "style_dp": style.dp, "text_mask": text_mask}
         )
@@ -213,6 +217,7 @@ class TextToSpeech:
     def __call__(
         self,
         text: str,
+        lang: str,
         style: Style,
         total_step: int,
         speed: float = 1.05,
@@ -221,11 +226,12 @@ class TextToSpeech:
         assert (
             style.ttl.shape[0] == 1
         ), "Single speaker text to speech only supports single style"
-        text_list = chunk_text(text)
+        max_len = 120 if lang == "ko" else 300
+        text_list = chunk_text(text, max_len=max_len)
         wav_cat = None
         dur_cat = None
         for text in text_list:
-            wav, dur_onnx = self._infer([text], style, total_step, speed)
+            wav, dur_onnx = self._infer([text], [lang], style, total_step, speed)
             if wav_cat is None:
                 wav_cat = wav
                 dur_cat = dur_onnx
@@ -238,9 +244,14 @@ class TextToSpeech:
         return wav_cat, dur_cat
 
     def batch(
-        self, text_list: list[str], style: Style, total_step: int, speed: float = 1.05
+        self,
+        text_list: list[str],
+        lang_list: list[str],
+        style: Style,
+        total_step: int,
+        speed: float = 1.05,
     ) -> tuple[np.ndarray, np.ndarray]:
-        return self._infer(text_list, style, total_step, speed)
+        return self._infer(text_list, lang_list, style, total_step, speed)
 
 
 def length_to_mask(lengths: np.ndarray, max_len: Optional[int] = None) -> np.ndarray:
@@ -365,11 +376,13 @@ def timer(name: str):
 
 
 def sanitize_filename(text: str, max_len: int) -> str:
-    """Sanitize filename by replacing non-alphanumeric characters with underscores"""
+    """Sanitize filename by replacing non-alphanumeric characters with underscores (supports Unicode)"""
     import re
 
     prefix = text[:max_len]
-    return re.sub(r"[^a-zA-Z0-9]", "_", prefix)
+    # \w matches Unicode word characters (letters, digits, underscore) with re.UNICODE
+    # We replace non-word characters except keeping existing underscores
+    return re.sub(r"[^\w]", "_", prefix, flags=re.UNICODE)
 
 
 def chunk_text(text: str, max_len: int = 300) -> list[str]:

rust/README.md

@@ -4,6 +4,12 @@ This guide provides examples for running TTS inference using Rust.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -54,19 +60,21 @@ Process multiple voice styles and texts at once:
 cargo run --release --bin example_onnx -- \
   --batch \
   --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요." \
+  --lang en,ko
 
 # Or using the binary directly
 ./target/release/example_onnx \
   --batch \
   --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요." \
+  --lang en,ko
 ```
 
 This will:
-- Generate speech for 2 different voice-text pairs
+- Generate speech for 2 different voice-text-language pairs
-- Use male voice (M1.json) for the first text
+- Use male voice (M1.json) for the first text in English
-- Use female voice (F1.json) for the second text
+- Use female voice (F1.json) for the second text in Korean
 - Process both samples in a single batch
 
 ### Example 3: High Quality Inference
@@ -120,14 +128,16 @@ This will:
 | `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
 | `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
 | `--n-test` | int | 4 | Number of times to generate each sample |
-| `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
+| `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s), comma-separated |
-| `--text` | str+ | (long default text) | Text(s) to synthesize |
+| `--text` | str+ | (long default text) | Text(s) to synthesize, pipe-separated |
+| `--lang` | str+ | `en` | Language(s) for synthesis, comma-separated (en, ko, es, pt, fr) |
 | `--save-dir` | str | `results` | Output directory |
 | `--batch` | flag | False | Enable batch mode (multiple text-style pairs, disables automatic chunking) |
 
 ## Notes
 
-- **Batch Processing**: When using `--batch`, the number of `--voice-style` files must match the number of `--text` entries
+- **Multilingual Support**: Use `--lang` to specify the language for each text. Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
+- **Batch Processing**: When using `--batch`, the number of `--voice-style`, `--text`, and `--lang` entries must match
 - **Automatic Chunking**: Without `--batch`, long texts are automatically split and concatenated with 0.3s pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

rust/src/example_onnx.rs

@@ -42,6 +42,10 @@ struct Args {
     #[arg(long, value_delimiter = '|', default_values_t = vec!["This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen.".to_string()])]
     text: Vec<String>,
 
+    /// Language(s) for synthesis (en, ko, es, pt, fr)
+    #[arg(long, value_delimiter = ',', default_values_t = vec!["en".to_string()])]
+    lang: Vec<String>,
+
     /// Output directory
     #[arg(long, default_value = "results")]
     save_dir: String,
@@ -61,6 +65,7 @@ fn main() -> Result<()> {
     let n_test = args.n_test;
     let voice_style_paths = &args.voice_style;
     let text_list = &args.text;
+    let lang_list = &args.lang;
     let save_dir = &args.save_dir;
     let batch = args.batch;
 
@@ -72,6 +77,13 @@ fn main() -> Result<()> {
                 text_list.len()
             );
         }
+        if lang_list.len() != text_list.len() {
+            anyhow::bail!(
+                "Number of languages ({}) must match number of texts ({})",
+                lang_list.len(),
+                text_list.len()
+            );
+        }
     }
 
     let bsz = voice_style_paths.len();
@@ -90,11 +102,11 @@ fn main() -> Result<()> {
 
         let (wav, duration) = if batch {
             timer("Generating speech from text", || {
-                text_to_speech.batch(text_list, &style, total_step, speed)
+                text_to_speech.batch(text_list, lang_list, &style, total_step, speed)
             })?
         } else {
             let (w, d) = timer("Generating speech from text", || {
-                text_to_speech.call(&text_list[0], &style, total_step, speed, 0.3)
+                text_to_speech.call(&text_list[0], &lang_list[0], &style, total_step, speed, 0.3)
             })?;
             (w, vec![d])
         };

rust/src/helper.rs

@@ -8,12 +8,19 @@ use serde_json;
 use std::fs::File;
 use std::io::BufReader;
 use std::path::Path;
-use anyhow::{Result, Context};
+use anyhow::{Result, Context, bail};
 use unicode_normalization::UnicodeNormalization;
 use hound::{WavWriter, WavSpec, SampleFormat};
 use rand_distr::{Distribution, Normal};
 use regex::Regex;
 
+// Available languages for multilingual TTS
+pub const AVAILABLE_LANGS: &[&str] = &["en", "ko", "es", "pt", "fr"];
+
+pub fn is_valid_lang(lang: &str) -> bool {
+    AVAILABLE_LANGS.contains(&lang)
+}
+
 // ============================================================================
 // Configuration Structures
 // ============================================================================
@@ -79,11 +86,11 @@ impl UnicodeProcessor {
         Ok(UnicodeProcessor { indexer })
     }
 
-    pub fn call(&self, text_list: &[String]) -> (Vec<Vec<i64>>, Array3<f32>) {
+    pub fn call(&self, text_list: &[String], lang_list: &[String]) -> Result<(Vec<Vec<i64>>, Array3<f32>)> {
-        let processed_texts: Vec<String> = text_list
+        let mut processed_texts: Vec<String> = Vec::new();
-            .iter()
+        for (text, lang) in text_list.iter().zip(lang_list.iter()) {
-            .map(|t| preprocess_text(t))
+            processed_texts.push(preprocess_text(text, lang)?);
-            .collect();
+        }
 
         let text_ids_lengths: Vec<usize> = processed_texts
             .iter()
@@ -108,16 +115,14 @@ impl UnicodeProcessor {
 
         let text_mask = get_text_mask(&text_ids_lengths);
 
-        (text_ids, text_mask)
+        Ok((text_ids, text_mask))
     }
 }
 
-pub fn preprocess_text(text: &str) -> String {
+pub fn preprocess_text(text: &str, lang: &str) -> Result<String> {
     // TODO: Need advanced normalizer for better performance
     let mut text: String = text.nfkd().collect();
 
-    // FIXME: this should be fixed for non-English languages
-
     // Remove emojis (wide Unicode range)
     let emoji_pattern = Regex::new(r"[\x{1F600}-\x{1F64F}\x{1F300}-\x{1F5FF}\x{1F680}-\x{1F6FF}\x{1F700}-\x{1F77F}\x{1F780}-\x{1F7FF}\x{1F800}-\x{1F8FF}\x{1F900}-\x{1F9FF}\x{1FA00}-\x{1FA6F}\x{1FA70}-\x{1FAFF}\x{2600}-\x{26FF}\x{2700}-\x{27BF}\x{1F1E6}-\x{1F1FF}]+").unwrap();
     text = emoji_pattern.replace_all(&text, "").to_string();
@@ -127,7 +132,6 @@ pub fn preprocess_text(text: &str) -> String {
         ("–", "-"),      // en dash
         ("‑", "-"),      // non-breaking hyphen
         ("—", "-"),      // em dash
-        ("¯", " "),      // macron
         ("_", " "),      // underscore
         ("\u{201C}", "\""),     // left double quote
         ("\u{201D}", "\""),     // right double quote
@@ -148,10 +152,6 @@ pub fn preprocess_text(text: &str) -> String {
         text = text.replace(from, to);
     }
 
-    // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-    let diacritics_pattern = Regex::new(r"[\u{0302}\u{0303}\u{0304}\u{0305}\u{0306}\u{0307}\u{0308}\u{030A}\u{030B}\u{030C}\u{0327}\u{0328}\u{0329}\u{032A}\u{032B}\u{032C}\u{032D}\u{032E}\u{032F}]").unwrap();
-    text = diacritics_pattern.replace_all(&text, "").to_string();
-
     // Remove special symbols
     let special_symbols = ["♥", "☆", "♡", "©", "\\"];
     for symbol in &special_symbols {
@@ -201,7 +201,15 @@ pub fn preprocess_text(text: &str) -> String {
         }
     }
 
-    text
+    // Validate language
+    if !is_valid_lang(lang) {
+        bail!("Invalid language: {}. Available: {:?}", lang, AVAILABLE_LANGS);
+    }
+
+    // Wrap text with language tags
+    text = format!("<{}>{}</{}>", lang, text, lang);
+
+    Ok(text)
 }
 
 pub fn text_to_unicode_values(text: &str) -> Vec<usize> {
@@ -505,15 +513,12 @@ where
 }
 
 pub fn sanitize_filename(text: &str, max_len: usize) -> String {
-    let text = if text.len() > max_len {
+    // Take first max_len characters (Unicode code points, not bytes)
-        &text[..max_len]
-    } else {
-        text
-    };
-
     text.chars()
+        .take(max_len)
         .map(|c| {
-            if c.is_ascii_alphanumeric() {
+            // is_alphanumeric() works with all Unicode letters and digits
+            if c.is_alphanumeric() {
                 c
             } else {
                 '_'
@@ -570,6 +575,7 @@ impl TextToSpeech {
     fn _infer(
         &mut self,
         text_list: &[String],
+        lang_list: &[String],
         style: &Style,
         total_step: usize,
         speed: f32,
@@ -577,7 +583,7 @@ impl TextToSpeech {
         let bsz = text_list.len();
 
         // Process text
-        let (text_ids, text_mask) = self.text_processor.call(text_list);
+        let (text_ids, text_mask) = self.text_processor.call(text_list, lang_list)?;
         
         let text_ids_array = {
             let text_ids_shape = (bsz, text_ids[0].len());
@@ -676,18 +682,20 @@ impl TextToSpeech {
     pub fn call(
         &mut self,
         text: &str,
+        lang: &str,
         style: &Style,
         total_step: usize,
         speed: f32,
         silence_duration: f32,
     ) -> Result<(Vec<f32>, f32)> {
-        let chunks = chunk_text(text, None);
+        let max_len = if lang == "ko" { 120 } else { 300 };
+        let chunks = chunk_text(text, Some(max_len));
         
         let mut wav_cat: Vec<f32> = Vec::new();
         let mut dur_cat: f32 = 0.0;
 
         for (i, chunk) in chunks.iter().enumerate() {
-            let (wav, duration) = self._infer(&[chunk.clone()], style, total_step, speed)?;
+            let (wav, duration) = self._infer(&[chunk.clone()], &[lang.to_string()], style, total_step, speed)?;
             
             let dur = duration[0];
             let wav_len = (self.sample_rate as f32 * dur) as usize;
@@ -712,11 +720,12 @@ impl TextToSpeech {
     pub fn batch(
         &mut self,
         text_list: &[String],
+        lang_list: &[String],
         style: &Style,
         total_step: usize,
         speed: f32,
     ) -> Result<(Vec<f32>, Vec<f32>)> {
-        self._infer(text_list, style, total_step, speed)
+        self._infer(text_list, lang_list, style, total_step, speed)
     }
 }
 

swift/README.md

@@ -4,6 +4,12 @@ This guide provides examples for running TTS inference using `example_onnx`.
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added `--speed` parameter to control speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -44,13 +50,14 @@ Process multiple voice styles and texts at once:
 .build/release/example_onnx \
   --batch \
   --voice-style assets/voice_styles/M1.json,assets/voice_styles/F1.json \
-  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."
+  --text "The sun sets behind the mountains, painting the sky in shades of pink and orange.|오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요." \
+  --lang en,ko
 ```
 
 This will:
-- Generate speech for 2 different voice-text pairs
+- Generate speech for 2 different voice-text-language triplets
-- Use male voice (M1.json) for the first text
+- Use male voice (M1.json) for the first English text
-- Use female voice (F1.json) for the second text
+- Use female voice (F1.json) for the second Korean text
 - Process both samples in a single batch
 
 ### Example 3: High Quality Inference
@@ -93,12 +100,23 @@ This will:
 | `--n-test` | int | 4 | Number of times to generate each sample |
 | `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
 | `--text` | str+ | (long default text) | Text(s) to synthesize |
+| `--lang` | str+ | `en` | Language(s) for synthesis (en, ko, es, pt, fr) |
 | `--save-dir` | str | `results` | Output directory |
-| `--batch` | flag | False | Enable batch mode (multiple text-style pairs, disables automatic chunking) |
+| `--batch` | flag | False | Enable batch mode (multiple text-style-lang triplets, disables automatic chunking) |
+
+## Multilingual Support
+
+Supertonic 2 supports multiple languages. Use the `--lang` argument to specify the language:
+
+- `en` - English (default)
+- `ko` - Korean (한국어)
+- `es` - Spanish (Español)
+- `pt` - Portuguese (Português)
+- `fr` - French (Français)
 
 ## Notes
 
-- **Batch Processing**: When using `--batch`, the number of `--voice-style` files must match the number of `--text` entries
+- **Batch Processing**: When using `--batch`, the number of `--voice-style`, `--text`, and `--lang` entries must match
 - **Automatic Chunking**: Without `--batch`, long texts are automatically split and concatenated with 0.3s pauses
 - **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
 - **GPU Support**: GPU mode is not supported yet

swift/Sources/ExampleONNX.swift

@@ -9,6 +9,7 @@ struct Args {
     var nTest: Int = 4
     var voiceStyle: [String] = ["assets/voice_styles/M1.json"]
     var text: [String] = ["This morning, I took a walk in the park, and the sound of the birds and the breeze was so pleasant that I stopped for a long time just to listen."]
+    var lang: [String] = ["en"]
     var saveDir: String = "results"
     var batch: Bool = false
 }
@@ -54,6 +55,11 @@ func parseArgs() -> Args {
                 args.text = arguments[i + 1].components(separatedBy: "|")
                 i += 1
             }
+        case "--lang":
+            if i + 1 < arguments.count {
+                args.lang = arguments[i + 1].components(separatedBy: ",")
+                i += 1
+            }
         case "--save-dir":
             if i + 1 < arguments.count {
                 args.saveDir = arguments[i + 1]
@@ -84,6 +90,10 @@ struct ExampleONNX {
                 print("Error: Number of voice styles (\(args.voiceStyle.count)) must match number of texts (\(args.text.count))")
                 return
             }
+            guard args.lang.count == args.text.count else {
+                print("Error: Number of languages (\(args.lang.count)) must match number of texts (\(args.text.count))")
+                return
+            }
         }
         
         let bsz = args.voiceStyle.count
@@ -108,13 +118,13 @@ struct ExampleONNX {
                 
                 if args.batch {
                     let result = try timer("Generating speech from text") {
-                        try textToSpeech.batch(args.text, style, args.totalStep, speed: args.speed)
+                        try textToSpeech.batch(args.text, args.lang, style, args.totalStep, speed: args.speed)
                     }
                     wav = result.wav
                     duration = result.duration
                 } else {
                     let result = try timer("Generating speech from text") {
-                        try textToSpeech.call(args.text[0], style, args.totalStep, speed: args.speed, silenceDuration: 0.3)
+                        try textToSpeech.call(args.text[0], args.lang[0], style, args.totalStep, speed: args.speed, silenceDuration: 0.3)
                     }
                     wav = result.wav
                     duration = [result.duration]

swift/Sources/Helper.swift

@@ -2,6 +2,14 @@ import Foundation
 import Accelerate
 import OnnxRuntimeBindings
 
+// MARK: - Available Languages
+
+let AVAILABLE_LANGS = ["en", "ko", "es", "pt", "fr"]
+
+func isValidLang(_ lang: String) -> Bool {
+    return AVAILABLE_LANGS.contains(lang)
+}
+
 // MARK: - Configuration Structures
 
 struct Config: Codable {
@@ -42,12 +50,16 @@ class UnicodeProcessor {
         self.indexer = try JSONDecoder().decode([Int64].self, from: data)
     }
     
-    func call(_ textList: [String]) -> (textIds: [[Int64]], textMask: [[[Float]]]) {
+    func call(_ textList: [String], _ langList: [String]) -> (textIds: [[Int64]], textMask: [[[Float]]]) {
-        let processedTexts = textList.map { preprocessText($0) }
+        var processedTexts = [String]()
+        for (i, text) in textList.enumerated() {
+            processedTexts.append(preprocessText(text, lang: langList[i]))
+        }
         
+        // Use unicodeScalars.count for correct length after NFKD decomposition
         var textIdsLengths = [Int]()
         for text in processedTexts {
-            textIdsLengths.append(text.count)
+            textIdsLengths.append(text.unicodeScalars.count)
         }
         
         let maxLen = textIdsLengths.max() ?? 0
@@ -71,11 +83,9 @@ class UnicodeProcessor {
     }
 }
 
-func preprocessText(_ text: String) -> String {
+func preprocessText(_ text: String, lang: String) -> String {
-    // TODO: Need advanced normalizer for better performance
+    // Use NFKD (decomposed) for proper Hangul Jamo decomposition
-    var text = text.precomposedStringWithCompatibilityMapping
+    var text = text.decomposedStringWithCompatibilityMapping
-
-    // FIXME: this should be fixed for non-English languages
 
     // Remove emojis (wide Unicode range)
     // Swift NSRegularExpression doesn't support Unicode escapes above \uFFFF
@@ -101,7 +111,6 @@ func preprocessText(_ text: String) -> String {
         "–": "-",      // en dash
         "‑": "-",      // non-breaking hyphen
         "—": "-",      // em dash
-        "¯": " ",      // macron
         "_": " ",      // underscore
         "\u{201C}": "\"",     // left double quote
         "\u{201D}": "\"",     // right double quote
@@ -122,11 +131,6 @@ func preprocessText(_ text: String) -> String {
         text = text.replacingOccurrences(of: old, with: new)
     }
 
-    // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-    let diacriticsPattern = try! NSRegularExpression(pattern: "[\\u0302\\u0303\\u0304\\u0305\\u0306\\u0307\\u0308\\u030A\\u030B\\u030C\\u0327\\u0328\\u0329\\u032A\\u032B\\u032C\\u032D\\u032E\\u032F]")
-    let diacriticsRange = NSRange(text.startIndex..., in: text)
-    text = diacriticsPattern.stringByReplacingMatches(in: text, range: diacriticsRange, withTemplate: "")
-
     // Remove special symbols
     let specialSymbols = ["♥", "☆", "♡", "©", "\\"]
     for symbol in specialSymbols {
@@ -179,6 +183,14 @@ func preprocessText(_ text: String) -> String {
         }
     }
 
+    // Validate language
+    guard isValidLang(lang) else {
+        fatalError("Invalid language: \(lang). Available: \(AVAILABLE_LANGS.joined(separator: ", "))")
+    }
+
+    // Wrap text with language tags
+    text = "<\(lang)>\(text)</\(lang)>"
+
     return text
 }
 
@@ -560,11 +572,11 @@ class TextToSpeech {
         self.sampleRate = cfgs.ae.sample_rate
     }
     
-    private func _infer(_ textList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
+    private func _infer(_ textList: [String], _ langList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
         let bsz = textList.count
         
         // Process text
-        let (textIds, textMask) = textProcessor.call(textList)
+        let (textIds, textMask) = textProcessor.call(textList, langList)
         
         // Flatten text IDs
         let textIdsFlat = textIds.flatMap { $0 }
@@ -688,14 +700,16 @@ class TextToSpeech {
         return (wav, duration)
     }
     
-    func call(_ text: String, _ style: Style, _ totalStep: Int, speed: Float = 1.05, silenceDuration: Float = 0.3) throws -> (wav: [Float], duration: Float) {
+    func call(_ text: String, _ lang: String, _ style: Style, _ totalStep: Int, speed: Float = 1.05, silenceDuration: Float = 0.3) throws -> (wav: [Float], duration: Float) {
-        let chunks = chunkText(text)
+        let maxLen = lang == "ko" ? 120 : 300
+        let chunks = chunkText(text, maxLen: maxLen)
+        let langList = Array(repeating: lang, count: chunks.count)
         
         var wavCat = [Float]()
         var durCat: Float = 0.0
         
         for (i, chunk) in chunks.enumerated() {
-            let result = try _infer([chunk], style, totalStep, speed: speed)
+            let result = try _infer([chunk], [langList[i]], style, totalStep, speed: speed)
             
             let dur = result.duration[0]
             let wavLen = Int(Float(sampleRate) * dur)
@@ -717,8 +731,8 @@ class TextToSpeech {
         return (wavCat, durCat)
     }
     
-    func batch(_ textList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
+    func batch(_ textList: [String], _ langList: [String], _ style: Style, _ totalStep: Int, speed: Float = 1.05) throws -> (wav: [Float], duration: [Float]) {
-        return try _infer(textList, style, totalStep, speed: speed)
+        return try _infer(textList, langList, style, totalStep, speed: speed)
     }
 }
 

test_all.sh

@@ -57,11 +57,13 @@ case $test_mode in
 esac
 echo ""
 
-# Batch inference test data - base variables
+# Batch inference test data - multilingual examples
 BATCH_VOICE_STYLE_1="assets/voice_styles/M1.json"
 BATCH_VOICE_STYLE_2="assets/voice_styles/F1.json"
 BATCH_TEXT_1="The sun sets behind the mountains, painting the sky in shades of pink and orange."
-BATCH_TEXT_2="The weather is beautiful and sunny outside. A gentle breeze makes the air feel fresh and pleasant."
+BATCH_TEXT_2="오늘 아침에 공원을 산책했는데, 새소리와 바람 소리가 너무 기분 좋았어요."
+BATCH_LANG_1="en"
+BATCH_LANG_2="ko"
 
 # Long-form inference test data
 LONGFORM_VOICE_STYLE="assets/voice_styles/M1.json"
@@ -179,7 +181,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "Python (default)" "py" "uv run example_onnx.py"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "Python (batch)" "py" "uv run example_onnx.py --batch --voice-style $BATCH_VOICE_STYLE_1 $BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1' '$BATCH_TEXT_2'"
+    run_test "Python (batch)" "py" "uv run example_onnx.py --batch --voice-style $BATCH_VOICE_STYLE_1 $BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1' '$BATCH_TEXT_2' --lang $BATCH_LANG_1 $BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "Python (long-form)" "py" "uv run example_onnx.py --voice-style $LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"
@@ -195,7 +197,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "JavaScript (default)" "nodejs" "node example_onnx.js"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "JavaScript (batch)" "nodejs" "node example_onnx.js --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "JavaScript (batch)" "nodejs" "node example_onnx.js --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2' --lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "JavaScript (long-form)" "nodejs" "node example_onnx.js --voice-style $LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"
@@ -212,7 +214,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "Go (default)" "go" "go run example_onnx.go helper.go"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "Go (batch)" "go" "go run example_onnx.go helper.go --batch -voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 -text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "Go (batch)" "go" "go run example_onnx.go helper.go --batch -voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 -text '$BATCH_TEXT_1|$BATCH_TEXT_2' -lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "Go (long-form)" "go" "go run example_onnx.go helper.go -voice-style $LONGFORM_VOICE_STYLE -text '$LONGFORM_TEXT'"
@@ -228,7 +230,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "Rust (default)" "rust" "cargo run --release"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "Rust (batch)" "rust" "cargo run --release -- --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "Rust (batch)" "rust" "cargo run --release -- --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2' --lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "Rust (long-form)" "rust" "cargo run --release -- --voice-style $LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"
@@ -244,7 +246,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "C# (default)" "csharp" "dotnet run --configuration Release"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "C# (batch)" "csharp" "dotnet run --configuration Release -- --batch --voice-style ../$BATCH_VOICE_STYLE_1,../$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "C# (batch)" "csharp" "dotnet run --configuration Release -- --batch --voice-style ../$BATCH_VOICE_STYLE_1,../$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2' --lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "C# (long-form)" "csharp" "dotnet run --configuration Release -- --voice-style ../$LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"
@@ -260,7 +262,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "Java (default)" "java" "mvn exec:java -q"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "Java (batch)" "java" "mvn exec:java -q -Dexec.args='--batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text \"$BATCH_TEXT_1|$BATCH_TEXT_2\"'"
+    run_test "Java (batch)" "java" "mvn exec:java -q -Dexec.args='--batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text \"$BATCH_TEXT_1|$BATCH_TEXT_2\" --lang $BATCH_LANG_1,$BATCH_LANG_2'"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "Java (long-form)" "java" "mvn exec:java -q -Dexec.args='--voice-style $LONGFORM_VOICE_STYLE --text \"$LONGFORM_TEXT\"'"
@@ -276,7 +278,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "Swift (default)" "swift" ".build/release/example_onnx"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "Swift (batch)" "swift" ".build/release/example_onnx --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "Swift (batch)" "swift" ".build/release/example_onnx --batch --voice-style $BATCH_VOICE_STYLE_1,$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2' --lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "Swift (long-form)" "swift" ".build/release/example_onnx --voice-style $LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"
@@ -292,7 +294,7 @@ if [ "$TEST_DEFAULT" = true ]; then
     run_test "C++ (default)" "cpp/build" "./example_onnx"
 fi
 if [ "$TEST_BATCH" = true ]; then
-    run_test "C++ (batch)" "cpp/build" "./example_onnx --batch --voice-style ../$BATCH_VOICE_STYLE_1,../$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2'"
+    run_test "C++ (batch)" "cpp/build" "./example_onnx --batch --voice-style ../$BATCH_VOICE_STYLE_1,../$BATCH_VOICE_STYLE_2 --text '$BATCH_TEXT_1|$BATCH_TEXT_2' --lang $BATCH_LANG_1,$BATCH_LANG_2"
 fi
 if [ "$TEST_LONGFORM" = true ]; then
     run_test "C++ (long-form)" "cpp/build" "./example_onnx --voice-style ../$LONGFORM_VOICE_STYLE --text '$LONGFORM_TEXT'"

web/README.md

@@ -4,6 +4,12 @@ This example demonstrates how to use Supertonic in a web browser using ONNX Runt
 
 ## 📰 Update News
 
+**2026.01.06** - 🎉 **Supertonic 2** released with multilingual support! Now supports English (`en`), Korean (`ko`), Spanish (`es`), Portuguese (`pt`), and French (`fr`). [Demo](https://huggingface.co/spaces/Supertone/supertonic-2) | [Models](https://huggingface.co/Supertone/supertonic-2)
+
+**2025.12.10** - Added [6 new voice styles](https://huggingface.co/Supertone/supertonic/tree/b10dbaf18b316159be75b34d24f740008fddd381) (M3, M4, M5, F3, F4, F5). See [Voices](https://supertone-inc.github.io/supertonic-py/voices/) for details
+
+**2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
+
 **2025.11.23** - Enhanced text preprocessing with comprehensive normalization, emoji removal, symbol replacement, and punctuation handling for improved synthesis quality.
 
 **2025.11.19** - Added speed control slider to adjust speech synthesis speed (default: 1.05, recommended range: 0.9-1.5).
@@ -14,9 +20,10 @@ This example demonstrates how to use Supertonic in a web browser using ONNX Runt
 
 - 🌐 Runs entirely in the browser (no server required for inference)
 - 🚀 WebGPU support with automatic fallback to WebAssembly
+- 🌍 Multilingual support: English (en), Korean (ko), Spanish (es), Portuguese (pt), French (fr)
 - ⚡ Pre-extracted voice styles for instant generation
 - 🎨 Modern, responsive UI
-- 🎭 Multiple voice style presets (2 Male, 2 Female)
+- 🎭 Multiple voice style presets (5 Male, 5 Female)
 - 💾 Download generated audio as WAV files
 - 📊 Detailed generation statistics (audio length, generation time)
 - ⏱️ Real-time progress tracking
@@ -48,20 +55,28 @@ This will start a local development server (usually at http://localhost:3000) an
 
 1. **Wait for Models to Load**: The app will automatically load models and the default voice style (M1)
 2. **Select Voice Style**: Choose from available voice presets
-   - **Male 1 (M1)**: Default male voice
+   - **Male 1-5 (M1-M5)**: Male voice styles
-   - **Male 2 (M2)**: Alternative male voice
+   - **Female 1-5 (F1-F5)**: Female voice styles
-   - **Female 1 (F1)**: Default female voice
+3. **Select Language**: Choose the language that matches your input text
-   - **Female 2 (F2)**: Alternative female voice
+   - **English (en)**: Default language
-3. **Enter Text**: Type or paste the text you want to convert to speech
+   - **한국어 (ko)**: Korean
-4. **Adjust Settings** (optional):
+   - **Español (es)**: Spanish
+   - **Português (pt)**: Portuguese
+   - **Français (fr)**: French
+4. **Enter Text**: Type or paste the text you want to convert to speech
+5. **Adjust Settings** (optional):
    - **Total Steps**: More steps = better quality but slower (default: 5)
-5. **Generate Speech**: Click the "Generate Speech" button
+6. **Generate Speech**: Click the "Generate Speech" button
-6. **View Results**: 
+7. **View Results**: 
    - See the full input text
    - View audio length and generation time statistics
    - Play the generated audio in the browser
    - Download as WAV file
 
+## Multilingual Support
+
+Supertonic 2 supports multiple languages. Make sure to select the correct language for your input text to get the best results. The model will automatically handle text preprocessing and pronunciation for the selected language.
+
 ## Technical Details
 
 ### Browser Compatibility
@@ -76,7 +91,7 @@ This demo uses:
 - The ONNX models must be accessible at `assets/onnx/` relative to the web root
 - Voice style JSON files must be accessible at `assets/voice_styles/` relative to the web root
 - Pre-extracted voice styles enable instant generation without audio processing
-- Four voice style presets are provided (M1, M2, F1, F2)
+- Ten voice style presets are provided (M1-M5, F1-F5)
 
 ## Troubleshooting
 

web/helper.js

@@ -1,5 +1,12 @@
 import * as ort from 'onnxruntime-web';
 
+// Available languages for multilingual TTS
+export const AVAILABLE_LANGS = ['en', 'ko', 'es', 'pt', 'fr'];
+
+export function isValidLang(lang) {
+    return AVAILABLE_LANGS.includes(lang);
+}
+
 /**
  * Unicode Text Processor
  */
@@ -8,8 +15,8 @@ export class UnicodeProcessor {
         this.indexer = indexer;
     }
 
-    call(textList) {
+    call(textList, langList) {
-        const processedTexts = textList.map(text => this.preprocessText(text));
+        const processedTexts = textList.map((text, i) => this.preprocessText(text, langList[i]));
         
         const textIdsLengths = processedTexts.map(text => text.length);
         const maxLen = Math.max(...textIdsLengths);
@@ -27,12 +34,10 @@ export class UnicodeProcessor {
         return { textIds, textMask };
     }
 
-    preprocessText(text) {
+    preprocessText(text, lang) {
         // TODO: Need advanced normalizer for better performance
         text = text.normalize('NFKD');
 
-        // FIXME: this should be fixed for non-English languages
-
         // Remove emojis (wide Unicode range)
         const emojiPattern = /[\u{1F600}-\u{1F64F}\u{1F300}-\u{1F5FF}\u{1F680}-\u{1F6FF}\u{1F700}-\u{1F77F}\u{1F780}-\u{1F7FF}\u{1F800}-\u{1F8FF}\u{1F900}-\u{1F9FF}\u{1FA00}-\u{1FA6F}\u{1FA70}-\u{1FAFF}\u{2600}-\u{26FF}\u{2700}-\u{27BF}\u{1F1E6}-\u{1F1FF}]+/gu;
         text = text.replace(emojiPattern, '');
@@ -42,12 +47,11 @@ export class UnicodeProcessor {
             '–': '-',
             '‑': '-',
             '—': '-',
-            '¯': ' ',
             '_': ' ',
-            '"': '"',
+            '\u201C': '"',  // left double quote "
-            '"': '"',
+            '\u201D': '"',  // right double quote "
-            '\u2018': "'",  // left single quote
+            '\u2018': "'",  // left single quote '
-            '\u2019': "'",  // right single quote
+            '\u2019': "'",  // right single quote '
             '´': "'",
             '`': "'",
             '[': ' ',
@@ -62,9 +66,6 @@ export class UnicodeProcessor {
             text = text.replaceAll(k, v);
         }
 
-        // Remove combining diacritics // FIXME: this should be fixed for non-English languages
-        text = text.replace(/[\u0302\u0303\u0304\u0305\u0306\u0307\u0308\u030A\u030B\u030C\u0327\u0328\u0329\u032A\u032B\u032C\u032D\u032E\u032F]/g, '');
-
         // Remove special symbols
         text = text.replace(/[♥☆♡©\\]/g, '');
 
@@ -106,6 +107,14 @@ export class UnicodeProcessor {
             text += '.';
         }
 
+        // Validate language
+        if (!isValidLang(lang)) {
+            throw new Error(`Invalid language: ${lang}. Available: ${AVAILABLE_LANGS.join(', ')}`);
+        }
+
+        // Wrap text with language tags
+        text = `<${lang}>${text}</${lang}>`;
+
         return text;
     }
 
@@ -150,11 +159,11 @@ export class TextToSpeech {
         this.sampleRate = cfgs.ae.sample_rate;
     }
 
-    async _infer(textList, style, totalStep, speed = 1.05, progressCallback = null) {
+    async _infer(textList, langList, style, totalStep, speed = 1.05, progressCallback = null) {
         const bsz = textList.length;
         
         // Process text
-        const { textIds, textMask } = this.textProcessor.call(textList);
+        const { textIds, textMask } = this.textProcessor.call(textList, langList);
         
         const textIdsFlat = new BigInt64Array(textIds.flat().map(x => BigInt(x)));
         const textIdsShape = [bsz, textIds[0].length];
@@ -259,16 +268,18 @@ export class TextToSpeech {
         return { wav, duration };
     }
 
-    async call(text, style, totalStep, speed = 1.05, silenceDuration = 0.3, progressCallback = null) {
+    async call(text, lang, style, totalStep, speed = 1.05, silenceDuration = 0.3, progressCallback = null) {
         if (style.ttl.dims[0] !== 1) {
             throw new Error('Single speaker text to speech only supports single style');
         }
-        const textList = chunkText(text);
+        const maxLen = lang === 'ko' ? 120 : 300;
+        const textList = chunkText(text, maxLen);
+        const langList = new Array(textList.length).fill(lang);
         let wavCat = [];
         let durCat = 0;
         
-        for (const chunk of textList) {
+        for (let i = 0; i < textList.length; i++) {
-            const { wav, duration } = await this._infer([chunk], style, totalStep, speed, progressCallback);
+            const { wav, duration } = await this._infer([textList[i]], [langList[i]], style, totalStep, speed, progressCallback);
             
             if (wavCat.length === 0) {
                 wavCat = wav;
@@ -284,8 +295,8 @@ export class TextToSpeech {
         return { wav: wavCat, duration: [durCat] };
     }
 
-    async batch(textList, style, totalStep, speed = 1.05, progressCallback = null) {
+    async batch(textList, langList, style, totalStep, speed = 1.05, progressCallback = null) {
-        return await this._infer(textList, style, totalStep, speed, progressCallback);
+        return await this._infer(textList, langList, style, totalStep, speed, progressCallback);
     }
 
     sampleNoisyLatent(duration, sampleRate, baseChunkSize, chunkCompress, latentDim) {

web/index.html

@@ -8,8 +8,8 @@
     </head>
     <body>
         <div class="container">
-            <h1>🎤 Supertonic</h1>
+            <h1>🎤 Supertonic 2</h1>
-            <p class="subtitle">Text-to-Speech with ONNX Runtime Web</p>
+            <p class="subtitle">Multilingual Text-to-Speech with ONNX Runtime Web</p>
 
             <div id="statusBox" class="status-box">
                 <div class="status-text-wrapper">
@@ -30,8 +30,25 @@
                         <select id="voiceStyleSelect">
                             <option value="assets/voice_styles/M1.json">Male 1 (M1)</option>
                             <option value="assets/voice_styles/M2.json">Male 2 (M2)</option>
+                            <option value="assets/voice_styles/M3.json">Male 3 (M3)</option>
+                            <option value="assets/voice_styles/M4.json">Male 4 (M4)</option>
+                            <option value="assets/voice_styles/M5.json">Male 5 (M5)</option>
                             <option value="assets/voice_styles/F1.json">Female 1 (F1)</option>
                             <option value="assets/voice_styles/F2.json">Female 2 (F2)</option>
+                            <option value="assets/voice_styles/F3.json">Female 3 (F3)</option>
+                            <option value="assets/voice_styles/F4.json">Female 4 (F4)</option>
+                            <option value="assets/voice_styles/F5.json">Female 5 (F5)</option>
+                        </select>
+                    </div>
+
+                    <div class="section">
+                        <label for="langSelect">Language:</label>
+                        <select id="langSelect">
+                            <option value="en" selected>English (en)</option>
+                            <option value="ko">한국어 (ko)</option>
+                            <option value="es">Español (es)</option>
+                            <option value="pt">Português (pt)</option>
+                            <option value="fr">Français (fr)</option>
                         </select>
                     </div>
 

web/main.js

@@ -24,6 +24,7 @@ let currentStylePath = DEFAULT_VOICE_STYLE_PATH;
 const textInput = document.getElementById('text');
 const voiceStyleSelect = document.getElementById('voiceStyleSelect');
 const voiceStyleInfo = document.getElementById('voiceStyleInfo');
+const langSelect = document.getElementById('langSelect');
 const totalStepInput = document.getElementById('totalStep');
 const speedInput = document.getElementById('speed');
 const generateBtn = document.getElementById('generateBtn');
@@ -188,12 +189,14 @@ async function generateSpeech() {
         
         const totalStep = parseInt(totalStepInput.value);
         const speed = parseFloat(speedInput.value);
+        const lang = langSelect.value;
         
         showStatus('ℹ️ <strong>Generating speech from text...</strong>');
         const tic = Date.now();
         
         const { wav, duration } = await textToSpeech.call(
-            text, 
+            text,
+            lang,
             currentStyle, 
             totalStep,
             speed,