supertonic 3

go/README.md

@@ -4,7 +4,7 @@ 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)
+**2026.04.29** - 🎉 **Supertonic 3** released with 31-language support, improved reading accuracy, and v2-compatible public ONNX assets. [Demo](https://huggingface.co/spaces/Supertone/supertonic-3) | [Models](https://huggingface.co/Supertone/supertonic-3)
 
 **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
 
@@ -30,6 +30,8 @@ This project uses Go modules for dependency management.
 brew install onnxruntime
 ```
 
+The Go example auto-detects Homebrew ONNX Runtime paths on both Apple Silicon and Intel Macs.
+
 **Linux:**
 ```bash
 # Download ONNX Runtime from GitHub releases
@@ -48,7 +50,7 @@ go mod download
 
 ### Configure ONNX Runtime Library Path (Optional)
 
-If the ONNX Runtime library is not in a standard location, set the environment variable:
+If the ONNX Runtime library is not in a standard or Homebrew location, set the environment variable:
 
 **Automatic Detection (Recommended):**
 
@@ -77,10 +79,10 @@ go run example_onnx.go helper.go
 ```
 
 This will use:
-- Voice style: `assets/voice_styles/M1.json`
+- Voice style: `../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."
 - Output directory: `results/`
-- Total steps: 5
+- Total steps: 8
 - Number of generations: 4
 
 ### Example 2: Batch Inference
@@ -88,7 +90,7 @@ Process multiple voice styles and texts at once:
 ```bash
 go run example_onnx.go helper.go \
   --batch \
-  -voice-style "assets/voice_styles/M1.json,assets/voice_styles/F1.json" \
+  -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"
 ```
@@ -104,12 +106,12 @@ Increase denoising steps for better quality:
 ```bash
 go run example_onnx.go helper.go \
   -total-step 10 \
-  -voice-style "assets/voice_styles/M1.json" \
+  -voice-style "../assets/voice_styles/M1.json" \
   -text "Increasing the number of denoising steps improves the output's fidelity and overall quality."
 ```
 
 This will:
-- Use 10 denoising steps instead of the default 5
+- Use 10 denoising steps instead of the default 8
 - Produce higher quality output at the cost of slower inference
 
 ### Example 4: Long-Form Inference
@@ -117,7 +119,7 @@ The system automatically chunks long texts into manageable segments, synthesizes
 
 ```bash
 go run example_onnx.go helper.go \
-  -voice-style "assets/voice_styles/M1.json" \
+  -voice-style "../assets/voice_styles/M1.json" \
   -text "This is a very long text that will be automatically split into multiple chunks. The system will process each chunk separately and then concatenate them together with natural pauses between segments. This ensures that even very long texts can be processed efficiently while maintaining natural speech flow and avoiding memory issues."
 ```
 
@@ -134,18 +136,18 @@ This will:
 | Argument | Type | Default | Description |
 |----------|------|---------|-------------|
 | `-use-gpu` | flag | false | Use GPU for inference (default: CPU) |
-| `-onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
-| `-total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
+| `-onnx-dir` | str | `../assets/onnx` | Path to ONNX model directory |
+| `-total-step` | int | 8 | 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), comma-separated |
+| `-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) |
+| `-lang` | str | `en` | Language(s) for synthesis, comma-separated; see the main README for all 31 codes |
 | `-save-dir` | str | `results` | Output directory |
 | `--batch` | flag | false | Enable batch mode (multiple text-style pairs, disables automatic chunking) |
 
 ## Notes
 
-- **Multilingual Support**: Use `-lang` to specify the language for each text. Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
+- **Multilingual Support**: Use `-lang` to specify the language for each text. Available: 31 languages; see the main README for the full list
 - **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
@@ -162,4 +164,3 @@ Then run it:
 ```bash
 ./tts_example -voice-style "../assets/voice_styles/M1.json" -text "Hello world"
 ```
-