Local, multilingual text-to-speech powered by Supertone's Supertonic ONNX model.
lang="na" auto-detect fallback. is user-verified to produce audible expression. and are weak/unconfirmed. All others fail silently.Requires the Python SDK and model assets. Install once:
pip install supertonic
First run auto-downloads ~400MB of ONNX models from Hugging Face into ~/.cache/supertonic3/.
from supertonic import TTS
tts = TTS(auto_download=True)
style = tts.get_voice_style(voice_name="M1")
wav, duration = tts.synthesize(
text="Your text here",
lang="en", # language code or "na" for auto-detect
voice_style=style,
total_steps=8, # quality: 5 (low) to 12 (high)
speed=1.0, # 0.7 (slow) to 2.0 (fast)
)
tts.save_audio(wav, "output.wav")
# Basic synthesis
supertonic tts "Hello world" -o output.wav
# Pick voice and quality
supertonic tts "Use a different voice." -o output.wav --voice F1 --steps 10
# Custom cloned voice
supertonic tts "Hello in my voice." -o output.wav --custom-style-path voices/my_voice.json
# Multilingual
supertonic tts "こんにちは" -o japanese.wav --lang ja
supertonic tts "Bonjour" -o french.wav --lang fr
cd ~/.openclaw/workspace/skills/supertonic-tts/scripts
source ~/.openclaw/workspace/.browser-use-venv/bin/activate
# Quick synthesis
python3 synthesize.py "Hello world" --voice M1 --output ~/hello.wav
# With expression tags (only <laugh> is confirmed to work)
python3 synthesize.py "You did it <laugh> I am so proud." --voice M5 --output laugh.wav
# Custom voice
python3 synthesize.py "Hello" --custom-style my_voice.json --output cloned.wav
# Japanese
python3 synthesize.py "こんにちは" --voice F3 --lang ja
# List voices
python3 list_voices.py
10 built-in voices: F1–F5 (female), M1–M5 (male).
Voice cloning: Record a short clip → upload to Voice Builder (online service, see privacy note in references/voices.md) → export JSON → load with get_voice_style_from_path().
See references/voices.md for voice descriptions and Voice Builder workflow.
> ⚠️ Mostly non-functional in practice
>
> Supertonic accepts inline self-closing tags, but only has been user-verified to produce a clearly audible expression (laughter burst). and may insert minor pauses but are not confirmed as audible breathing/sighing sounds.
>
> Do not rely on tags for expression. Tested tags that failed to produce audible effect include: , , , , , , , , , , , , , , , , , , .
Correct syntax (self-closing, inline):
text = "You did it <laugh> I am so proud."
Reliable alternative for emotion: explicit language + speed modulation:
| Emotion | Technique |
|---|---|
| --------- | ----------- |
| Happy | Upbeat words + speed=1.1 |
| Sad | Subdued words + speed=0.85 |
| Excited | Exclamations + speed=1.15 |
| Urgent | Short imperatives + speed=1.2 |
See references/expression-tags.md for full testing results.
| Param | Range | Default | What It Does |
|---|---|---|---|
| ------- | ------- | --------- | ------------- |
total_steps | 5–12 | 8 | Quality vs speed tradeoff |
speed | 0.7–2.0 | 1.0 | Speech rate multiplier |
max_chunk_length | any | 300 | Break long text into chunks (120 for Korean) |
silence_duration | any | 0.3 | Pause between chunks (seconds) |
lang | ISO 639-1 or "na" | "en" | "na" = language-agnostic auto-detect |
verbose | True/False | False | Show detailed progress |
31 languages + na (language-agnostic auto-detect). See references/languages.md for all codes.
(wav_array, duration_array)wav.shape = (1, num_samples)duration[0] = length in secondsSupertonic runs across: Python, Node.js, Browser (WebGPU), Java, C++, C#, Go, Swift, iOS, Rust, Flutter.
scripts/synthesize.py — CLI for quick text-to-speech (supports custom voices)scripts/list_voices.py — Available voices and metadatareferences/voices.md — Voice descriptions, selection guide, Voice Builder workflowreferences/expression-tags.md — All tags, examples, caveatsreferences/languages.md — Supported language codesreferences/deployment.md — Multi-runtime deployment options共 2 个版本