supertonic 3
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haeon
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py/README.md
28
py/README.md
@@ -4,7 +4,7 @@ This guide provides examples for running TTS inference using `example_onnx.py`.
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## 📰 Update News
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**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)
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**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)
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**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.
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@@ -46,17 +46,17 @@ uv run example_onnx.py
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```
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This will use:
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- Voice style: `assets/voice_styles/M1.json`
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- Voice style: `../assets/voice_styles/M1.json`
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- 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."
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- Output directory: `results/`
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- Total steps: 5
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- Total steps: 8
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- Number of generations: 4
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### Example 2: Batch Inference
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Process multiple voice styles and texts at once:
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```bash
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uv run example_onnx.py \
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--voice-style assets/voice_styles/M1.json assets/voice_styles/F1.json \
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--voice-style ../assets/voice_styles/M1.json ../assets/voice_styles/F1.json \
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--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." \
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--lang en ko \
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--batch
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@@ -74,19 +74,19 @@ Increase denoising steps for better quality:
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```bash
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uv run example_onnx.py \
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--total-step 10 \
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--voice-style assets/voice_styles/M1.json \
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--voice-style ../assets/voice_styles/M1.json \
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--text "Increasing the number of denoising steps improves the output's fidelity and overall quality."
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```
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This will:
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- Use 10 denoising steps instead of the default 5
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- Use 10 denoising steps instead of the default 8
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- Produce higher quality output at the cost of slower inference
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### Example 4: Long-Form Inference
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For long texts, the system automatically chunks the text into manageable segments and generates a single audio file:
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```bash
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uv run example_onnx.py \
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--voice-style assets/voice_styles/M1.json \
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--voice-style ../assets/voice_styles/M1.json \
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--text "Once upon a time, in a small village nestled between rolling hills, there lived a young artist named Clara. Every morning, she would wake up before dawn to capture the first light of day. The golden rays streaming through her window inspired countless paintings. Her work was known throughout the region for its vibrant colors and emotional depth. People from far and wide came to see her gallery, and many said her paintings could tell stories that words never could."
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```
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@@ -103,13 +103,13 @@ Control the speed of speech synthesis:
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```bash
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# Faster speech (speed > 1.0)
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uv run example_onnx.py \
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--voice-style assets/voice_styles/F2.json \
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--voice-style ../assets/voice_styles/F2.json \
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--text "This text will be synthesized at a faster pace." \
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--speed 1.2
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# Slower speech (speed < 1.0)
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uv run example_onnx.py \
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--voice-style assets/voice_styles/M2.json \
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--voice-style ../assets/voice_styles/M2.json \
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--text "This text will be synthesized at a slower, more deliberate pace." \
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--speed 0.9
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```
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@@ -125,20 +125,20 @@ This will:
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| Argument | Type | Default | Description |
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|----------|------|---------|-------------|
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| `--use-gpu` | flag | False | Use GPU for inference (with CPU fallback) |
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| `--onnx-dir` | str | `assets/onnx` | Path to ONNX model directory |
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| `--total-step` | int | 5 | Number of denoising steps (higher = better quality, slower) |
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| `--onnx-dir` | str | `../assets/onnx` | Path to ONNX model directory |
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| `--total-step` | int | 8 | Number of denoising steps (higher = better quality, slower) |
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| `--speed` | float | 1.05 | Speech speed factor (higher = faster, lower = slower) |
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| `--n-test` | int | 4 | Number of times to generate each sample |
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| `--voice-style` | str+ | `assets/voice_styles/M1.json` | Voice style file path(s) |
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| `--voice-style` | str+ | `../assets/voice_styles/M1.json` | Voice style file path(s) |
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| `--text` | str+ | (long default text) | Text(s) to synthesize |
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| `--lang` | str+ | `en` | Language(s) for text(s): `en`, `ko`, `es`, `pt`, `fr` |
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| `--lang` | str+ | `en` | Language(s) for text(s); see the main README for all 31 codes |
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| `--save-dir` | str | `results` | Output directory |
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| `--batch` | flag | False | Enable batch mode (disables automatic text chunking) |
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## Notes
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- **Batch Processing**: The number of `--voice-style` files must match the number of `--text` entries
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- **Multilingual Support**: Use `--lang` to specify language(s). Available: `en` (English), `ko` (Korean), `es` (Spanish), `pt` (Portuguese), `fr` (French)
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- **Multilingual Support**: Use `--lang` to specify language(s). Available: 31 languages; see the main README for the full list
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- **Long-Form Inference**: Without `--batch` flag, long texts are automatically chunked and combined into a single audio file with natural pauses
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- **Quality vs Speed**: Higher `--total-step` values produce better quality but take longer
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- **GPU Support**: GPU mode is not supported yet
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@@ -18,13 +18,13 @@ def parse_args():
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parser.add_argument(
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"--onnx-dir",
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type=str,
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default="assets/onnx",
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default="../assets/onnx",
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help="Path to ONNX model directory",
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)
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# Synthesis parameters
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parser.add_argument(
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"--total-step", type=int, default=5, help="Number of denoising steps"
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"--total-step", type=int, default=8, help="Number of denoising steps"
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)
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parser.add_argument(
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"--speed",
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@@ -44,7 +44,7 @@ def parse_args():
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"--voice-style",
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type=str,
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nargs="+",
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default=["assets/voice_styles/M1.json"],
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default=["../assets/voice_styles/M1.json"],
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help="Voice style file path(s). Can specify multiple files for batch processing",
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)
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parser.add_argument(
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@@ -10,7 +10,7 @@ import onnxruntime as ort
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import re
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AVAILABLE_LANGS = ["en", "ko", "es", "pt", "fr"]
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AVAILABLE_LANGS = ["en", "ko", "ja", "ar", "bg", "cs", "da", "de", "el", "es", "et", "fi", "fr", "hi", "hr", "hu", "id", "it", "lt", "lv", "nl", "pl", "pt", "ro", "ru", "sk", "sl", "sv", "tr", "uk", "vi"]
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class UnicodeProcessor:
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@@ -226,7 +226,7 @@ class TextToSpeech:
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assert (
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style.ttl.shape[0] == 1
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), "Single speaker text to speech only supports single style"
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max_len = 120 if lang == "ko" else 300
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max_len = 120 if lang in ("ko", "ja") else 300
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text_list = chunk_text(text, max_len=max_len)
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wav_cat = None
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dur_cat = None
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