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docs: revamp README for Supertonic 3

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- Move shields.io badges below banner, keep only latest v3 set
- Add Trendshift badge (centered)
- Add ✨ Highlights section absorbing former "Why Supertonic?" content
- List 31 supported languages with `lang="na"` note for unknown-language input
- Rename runtime examples section to "Programming Language Support"
- Add Minimax-MLS-test detailed WER/CER table (collapsible) with VoxCPM2, OmniVoice, Qwen3-TTS, Supertonic 2/3; mark ar/hi/ja/ko as CER
- Add "Models & Versions" comparison table covering v1/v2/v3

Co-Authored-By: Claude Opus 4.7 (1M context) <noreply@anthropic.com>
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2026-05-15 18:25:37 +09:00
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@@ -1,16 +1,38 @@
# Supertonic — Lightning Fast, On-Device, Accurate TTS
[![v3 Demo](https://img.shields.io/badge/🤗%20v3-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic-3)
[![v3 Models](https://img.shields.io/badge/🤗%20v3-Models-blue)](https://huggingface.co/Supertone/supertonic-3)
[![v2 Branch](https://img.shields.io/badge/v2-release%2Fsupertonic--2-lightgrey)](https://github.com/supertone-inc/supertonic/tree/release/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/Supertonic3_HeroImage.png" alt="Supertonic 3 Banner">
</p>
**Supertonic** is a lightning-fast, on-device text-to-speech system designed for local inference with minimal overhead. Powered by ONNX Runtime, it runs entirely on your device—no cloud, no API calls, no privacy concerns.
[![GitHub | Official Repo](https://img.shields.io/badge/GitHub-Official%20Repo-black?logo=github)](https://github.com/supertone-inc/supertonic)
[![Models](https://img.shields.io/badge/🤗%20Hugging%20Face-Models-blue)](https://huggingface.co/Supertone/supertonic-3)
[![Runs Locally via WebGPU](https://img.shields.io/badge/🤗%20Hugging%20Face-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic-3)
[![DemoPage | Audio Samples](https://img.shields.io/badge/DemoPage-Audio%20Samples-F5D90A?labelColor=0B0C0E)](https://supertonic3.github.io/)
[![Voice Builder | Cloning Demo](https://img.shields.io/badge/Voice%20Builder-Cloning%20Demo-3457D5?logo=soundcloud&logoColor=white)](https://supertonic.supertone.ai/voice_builder)
[![GitHub | Python Package](https://img.shields.io/badge/GitHub-Python%20Package-black?logo=github)](https://github.com/supertone-inc/supertonic-py)
[![Docs | Python PyPI](https://img.shields.io/badge/Docs-Python%20PyPI-blue?logo=readthedocs&logoColor=white)](https://github.com/supertone-inc/supertonic-py)
<p align="center">
<a href="https://trendshift.io/repositories/15657" target="_blank"><img src="https://trendshift.io/api/badge/repositories/15657" alt="supertone-inc%2Fsupertonic | Trendshift" style="width: 250px; height: 55px;" width="250" height="55"/></a>
</p>
**Supertonic** is a lightning-fast, on-device multilingual text-to-speech system designed for local inference with minimal overhead. Powered by ONNX Runtime, it runs entirely on your device—no cloud, no API calls, no privacy concerns.
### ✨ Highlights
- ⚡ **Blazingly Fast** — Low-latency, real-time synthesis across desktop, browser, mobile, and edge — fast enough to turn an entire webpage into audio in under a second
- 🌍 **31-Language Multilingual** — Synthesize directly from text across 31 languages, or pass `lang="na"` to let Supertonic process the text language-agnostically when you don't know the input language — no separate language adapters needed
- 🪶 **99M-Parameter Open-Weight Model** — A compact, fully open-weight checkpoint — a fraction of the size of 0.7B–2B class open TTS systems — for smaller downloads, faster cold starts, and lower memory footprint
- 📱 **Edge-Device Ready** — Runs locally on desktop, mobile, browsers, and resource-constrained hardware like Raspberry Pi or e-readers, with zero network dependency, complete privacy, and no GPU required
- 🔊 **44.1kHz High-Quality Audio** — Outputs studio-grade 44.1kHz 16-bit WAV directly, ready for production playback without any external upsampler
- 🎭 **Expression Tags** — 10 inline tags (e.g. `<laugh>`, `<breath>`, `<sigh>`) bring natural human nuance into generated speech without prompt engineering or reference audio
- 🛠️ **Multi-Runtime SDKs** — Ready-to-use examples through ONNX Runtime across Python, Node.js, Browser (WebGPU), Java, C++, C#, Go, Swift, iOS, Rust, and Flutter
### 🌍 Supported Languages (31)
Arabic (`ar`), Bulgarian (`bg`), Croatian (`hr`), Czech (`cs`), Danish (`da`), Dutch (`nl`), English (`en`), Estonian (`et`), Finnish (`fi`), French (`fr`), German (`de`), Greek (`el`), Hindi (`hi`), Hungarian (`hu`), Indonesian (`id`), Italian (`it`), Japanese (`ja`), Korean (`ko`), Latvian (`lv`), Lithuanian (`lt`), Polish (`pl`), Portuguese (`pt`), Romanian (`ro`), Russian (`ru`), Slovak (`sk`), Slovenian (`sl`), Spanish (`es`), Swedish (`sv`), Turkish (`tr`), Ukrainian (`uk`), Vietnamese (`vi`)
> **Not sure which language your text is in?** Pass `lang="na"` and Supertonic will handle the input in a language-agnostic way — no explicit language tag required.
### 📰 Update News
@@ -22,6 +44,8 @@
- **2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
- **2025.11.24** - Added Flutter SDK support with macOS compatibility
---
## Quick Start
Install the Python SDK and generate speech immediately. On the first run, Supertonic downloads the model assets from Hugging Face automatically.
@@ -40,8 +64,15 @@ tts = TTS(auto_download=True)
style = tts.get_voice_style(voice_name="M1")
text = "A gentle breeze moved through the open window while everyone listened to the story."
wav, duration = tts.synthesize(text, voice_style=style, lang="en")
text = "Supertonic is a lightning fast, on-device TTS system."
wav, duration = tts.synthesize(
text=text,
lang="en", # Language code (e.g., "en", "ko", "na" for language-agnostic)
voice_style=style, # Voice style object
total_steps=8, # Quality: 5 (low) to 12 (high), default 8 (medium)
speed=1.05, # Speed: 0.7 (slow) to 2.0 (fast)
)
tts.save_audio(wav, "output.wav")
print(f"Generated {duration:.2f}s of audio")
@@ -157,13 +188,14 @@ In Xcode: Targets → ExampleiOSApp → Signing: select your Team, then choose y
</details>
---
### Technical Details
- **Runtime**: ONNX Runtime for cross-platform inference
- **Browser Support**: onnxruntime-web for client-side inference
- **Batch Processing**: Supports batch inference for improved throughput
- **Audio Output**: Outputs 16-bit WAV files
- **Audio Output**: Outputs 44.1kHz 16-bit WAV files
## Performance Highlights
@@ -175,7 +207,40 @@ Supertonic 3 is designed for practical on-device inference: compact enough to ru
<img src="img/metrics/s3_vs_measured_wer_range_voxcpm2.png" alt="Supertonic 3 reading accuracy compared with measured model ranges and VoxCPM2">
</p>
Across measured languages, Supertonic 3 stays within a competitive WER/CER range against much larger open TTS models such as VoxCPM2, while preserving a lightweight on-device deployment path. Asterisked languages use CER; the others use WER.
Evaluated on the **[Minimax-MLS-test](https://huggingface.co/datasets/MiniMaxAI/TTS-MLS-Test) benchmark**, Supertonic 3 stays within a competitive WER/CER range against much larger open TTS models such as VoxCPM2, while preserving a lightweight on-device deployment path. Asterisked languages (`*`) use CER; the others use WER.
<details>
<summary><b>📊 Detailed per-language results (WER / CER*)</b></summary>
<br>
| Lang | VoxCPM2 | OmniVoice | Qwen3-TTS | Supertonic 2 | **Supertonic 3** |
|---|:---:|:---:|:---:|:---:|:---:|
| arabic\* | 4.14 | 1.74 | — | — | **2.14** |
| czech | 23.73 | 2.40 | — | — | **3.02** |
| dutch | 0.84 | 0.77 | — | — | **1.47** |
| english | 2.11 | 2.02 | 2.25 | 2.52 | **2.06** |
| finnish | 2.29 | 3.94 | — | — | **5.40** |
| french | 4.41 | 4.74 | 3.82 | 5.09 | **4.89** |
| german | 0.85 | 0.96 | 0.52 | — | **0.86** |
| greek | 3.22 | 2.96 | — | — | **3.54** |
| hindi\* | 5.85 | 5.14 | — | — | **5.34** |
| indonesian | 1.25 | 1.67 | — | — | **1.34** |
| italian | 1.74 | 1.29 | 1.40 | — | **1.75** |
| japanese\* | 3.35 | 3.81 | 3.67 | — | **4.61** |
| korean\* | 4.70 | 3.22 | 4.07 | 3.65 | **3.26** |
| polish | 1.30 | 0.64 | — | — | **1.63** |
| portuguese | 1.74 | 1.40 | 1.21 | 1.52 | **2.48** |
| romanian | 22.39 | 2.29 | — | — | **2.19** |
| russian | 3.31 | 4.53 | 4.48 | — | **3.99** |
| spanish | 1.34 | 0.99 | 0.75 | 1.81 | **1.13** |
| turkish | 0.88 | 2.18 | — | — | **1.00** |
| ukrainian | 5.85 | 0.71 | — | — | **1.23** |
| vietnamese | 1.48 | 0.79 | — | — | **4.49** |
> Lower is better. `*` indicates CER (character error rate); all other rows use WER (word error rate). Dashes (`—`) indicate the model does not officially support the language or no result is available.
</details>
### Supertonic 2 to Supertonic 3
@@ -223,29 +288,7 @@ Turns any webpage into audio in under one second, delivering lightning-fast, on-
https://github.com/user-attachments/assets/cc8a45fc-5c3e-4b2c-8439-a14c3d00d91c
## Why Supertonic?
- **Blazingly Fast**: Optimized for low-latency, on-device speech generation across desktop, browser, and edge deployments
- **Lightweight**: Compact ONNX assets designed for efficient local execution
- **On-Device Capable**: Complete privacy and zero network dependency
- **Accurate Reading**: Improved reading stability with fewer repeat and skip failures
- **Expressive Tags**: Supports simple expression tags such as `<laugh>`, `<breath>`, and `<sigh>`
- **Flexible Deployment**: Ready-to-use examples across Python, JavaScript, browser, mobile, and native runtimes
## Language Support
Supertonic 3 supports 31 languages:
| Code | Language | Code | Language | Code | Language | Code | Language |
|------|----------|------|----------|------|----------|------|----------|
| `en` | English | `ko` | Korean | `ja` | Japanese | `ar` | Arabic |
| `bg` | Bulgarian | `cs` | Czech | `da` | Danish | `de` | German |
| `el` | Greek | `es` | Spanish | `et` | Estonian | `fi` | Finnish |
| `fr` | French | `hi` | Hindi | `hr` | Croatian | `hu` | Hungarian |
| `id` | Indonesian | `it` | Italian | `lt` | Lithuanian | `lv` | Latvian |
| `nl` | Dutch | `pl` | Polish | `pt` | Portuguese | `ro` | Romanian |
| `ru` | Russian | `sk` | Slovak | `sl` | Slovenian | `sv` | Swedish |
| `tr` | Turkish | `uk` | Ukrainian | `vi` | Vietnamese | | |
## Programming Language Support
We provide ready-to-use TTS inference examples across multiple ecosystems:
@@ -373,6 +416,19 @@ Supertonic is designed to handle complex, real-world text inputs that contain na
| **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) |
## Models & Versions
| | **Supertonic 3** | Supertonic 2 | Supertonic 1 |
|---|:---:|:---:|:---:|
| **Status** | 🟢 Latest | Stable | Legacy |
| **Parameters** | ~99M | ~66M | ~66M |
| **Languages** | 31 | 5 | 1 (en) |
| **Expression Tags** | ✅ 10 tags | — | — |
| **Code** | [main](https://github.com/supertone-inc/supertonic) | [release/supertonic-2](https://github.com/supertone-inc/supertonic/tree/release/supertonic-2) | — |
| **Weights** | [🤗 HF](https://huggingface.co/Supertone/supertonic-3) | [🤗 HF](https://huggingface.co/Supertone/supertonic-2) | [🤗 HF](https://huggingface.co/Supertone/supertonic) |
| **Interactive Demo** | [🤗 Space](https://huggingface.co/spaces/Supertone/supertonic-3) | [🤗 Space](https://huggingface.co/spaces/Supertone/supertonic-2) | [🤗 Space](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo) |
| **Audio Samples** | [DemoPage](https://supertonic3.github.io/) | — | [DemoPage](https://supertonictts.github.io/) |
## 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: