This repository is archived. Development and support have ended.
The code remains available for reference under the terms of the LICENSE. No updates, bug fixes, security patches, or support will be provided, and issues and pull requests are no longer monitored. The software is provided "AS IS" as set forth in the license, without any warranty or ongoing responsibility of the original authors.
Archive locations
The source code is preserved under the supertone-oss-archive GitHub organization.
Model downloads now use the supertone-oss-archive Hugging Face namespace:
See Quick Start to download the archived models and run locally.
Code and model weights retain their respective licenses.
This archive does not include hosted demos or Voice Builder services.
Supertonic — Lightning Fast, On-Device, Accurate TTS
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.
Historical release notes
These entries describe past releases. Hosted services and support offers mentioned
here are no longer provided by this archive. Follow the archive setup guide.
- 2026.05.20 - Supertonic 3 is now officially supported in Supertone Play and the Supertone API. Visit Play or the API if you want a managed content creation workflow with diverse preset voices and zero-shot voice cloning.
- 2026.05.18 - Python SDK v1.3.1 adds
supertonic serve, a local HTTP server with native /v1/tts and OpenAI-compatible /v1/audio/speech endpoints. See the serve documentation.
- 2026.05.18 - Voice Builder now supports Supertonic 3. Create a permanent custom voice profile for Supertonic and download version-specific JSON files for both Supertonic 2 and Supertonic 3. If you already created a Supertonic 2 voice, the matching Supertonic 3 JSON is now available from My Page.
- 2026.04.29 - 🎉 Supertonic 3 released with 31-language support, improved reading accuracy, fewer repeat/skip failures, and v2-compatible public ONNX assets. Demo | Models
- 2026.01.22 - Voice Builder is now live! Turn your voice into a deployable, edge-native TTS with permanent ownership.
- 2026.01.06 - 🎉 Supertonic 2 released with 5-language support. The v2 code path is preserved on the
release/supertonic-2 branch.
- 2025.12.10 - Added
supertonic PyPI package! Install via pip install supertonic. For details, visit supertonic-py documentation
- 2025.12.10 - Added 6 new voice styles (M3, M4, M5, F3, F4, F5). See Voices for details
- 2025.12.08 - Optimized ONNX models via OnnxSlim now available on Hugging Face Models
- 2025.11.24 - Added Flutter SDK support with macOS compatibility
Quick Start
Use the examples in this repository with model files downloaded explicitly from
the archive. No Hugging Face login, hosted demo, or original Supertone service is
required. These instructions use Supertonic 3.
Use Python 3.11 in a virtual environment:
git clone https://github.com/supertone-oss-archive/supertonic.git
cd supertonic
python3.11 -m venv .venv
source .venv/bin/activate
python -m pip install huggingface_hub
On Windows, activate the environment with .venv\Scripts\Activate.ps1 in PowerShell.
2. Download the archived model
hf download supertone-oss-archive/supertonic-3 \
--revision aafc6e32416a594460b32413efc49d7fe4ce6d46 \
--local-dir assets
This downloads the ONNX models, configuration, and preset voice styles to assets/.
The revision pins the archived snapshot. Git LFS is not needed for this download method.
See Models & Versions for the archived Supertonic 1 and 2 weights.
3. Generate speech locally
python -m pip install -r py/requirements.txt
cd py
python example_onnx.py --n-test 1 --text "This speech was generated locally with the archived Supertonic model." --lang en
The generated WAV file is saved in py/results/. After dependencies and models
have been downloaded, this example performs inference locally without a network connection.
See Python examples for voice selection, batch synthesis, and other options.
Optional Python SDK
Older releases of the supertonic Python package may still use the original
Supertone Hugging Face namespace for automatic downloads. Download assets/
as above and pass model_dir with auto_download=False instead.
To use the preserved SDK source with Supertonic 3 support, run these commands
from the repository root in the same virtual environment:
python -m pip install "git+https://github.com/supertone-oss-archive/supertonic-py.git@df0f9686dac7fbbde391b759e2ee5286a3737622"
python py/example_pypi.py
The SDK example uses the local assets/ directory and does not download models.
The archived local server guide
is available for reference; the ONNX example above is the default archive setup.
Getting Started in Other Runtimes
Download the same assets/ directory from the repository root before running
the examples below. The language examples read these local files.
Some language examples need native runtimes:
- Go: install the ONNX Runtime C library. On macOS,
brew install onnxruntime.
- Java: use a JDK, not just a JRE. On macOS,
brew install openjdk@17.
- C#: targets .NET 9 and allows major-version roll-forward.
Other Runtime Examples
Run Supertonic in other languages and platforms
Node.js Example (Details)
cd nodejs
npm install
npm start
Browser Example (Details)
cd web
npm install
npm run dev
Java Example (Details)
cd java
mvn clean install
mvn exec:java
C++ Example (Details)
cd cpp
mkdir build && cd build
cmake .. && cmake --build . --config Release
./example_onnx
C# Example (Details)
cd csharp
dotnet restore
dotnet run
Go Example (Details)
cd go
go mod download
go run example_onnx.go helper.go
Swift Example (Details)
cd swift
swift build -c release
.build/release/example_onnx
Rust Example (Details)
cd rust
cargo build --release
./target/release/example_onnx
iOS Example (Details)
cd ios/ExampleiOSApp
xcodegen generate
open ExampleiOSApp.xcodeproj
In Xcode: Targets → ExampleiOSApp → Signing: select your Team, then choose your iPhone as run destination and build.
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 44.1kHz 16-bit WAV files
Supertonic 3 is designed for practical on-device inference: compact enough to run locally, while staying competitive with much larger open TTS systems.
Reading Accuracy
Evaluated on the Minimax-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.
📊 Detailed per-language results (WER / CER*)
| 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.
Supertonic 2 to Supertonic 3
Compared with Supertonic 2, Supertonic 3 reduces repeat and skip failures, improves speaker similarity across the shared-language set, and expands language coverage from 5 to 31 languages. It keeps the v2-compatible public ONNX interface, so existing integrations can move to v3 with the same inference contract.
Supertonic 3 runs fast on CPU, even compared with larger baselines measured on A100 GPU, and uses substantially less memory. The open-weight fixed-voice setting does not require a GPU, which makes local, browser, and edge deployment much easier.
Model Size
At about 99M parameters across the public ONNX assets, Supertonic 3 is much smaller than 0.7B to 2B class open TTS systems. The smaller model size is a practical advantage for download size, startup time, and on-device inference.
Voice Cloning
This open-weight repository focuses on fixed-voice, local TTS and does not include an official voice-cloning pipeline. If you want to bring your own voice to local Supertonic deployment, Voice Builder turns a short reference recording into version-specific JSON files for Supertonic 2 and Supertonic 3, so the same custom voice can move with you across supported Supertonic versions.
For a managed creation workflow, Supertonic 3 is now officially available in Supertone Play and the Supertone API. Use them when you want hosted content creation tools, diverse commercially usable preset voices, zero-shot voice cloning, or API-based integration without managing local model files. You can also listen to Supertonic 3 zero-shot samples on the official showcase.
Demo
Run locally: Follow Quick Start with the archived weights.
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
Chrome Extension
Turns any webpage into audio in under one second, delivering lightning-fast, on-device text-to-speech with zero network dependency—free, private, and effortless:
https://github.com/user-attachments/assets/cc8a45fc-5c3e-4b2c-8439-a14c3d00d91c
Programming Language Support
We provide ready-to-use TTS inference examples across multiple ecosystems:
| Language/Platform |
Path |
Description |
| Python |
py/ |
ONNX Runtime inference |
| Node.js |
nodejs/ |
Server-side JavaScript |
| Browser |
web/ |
WebGPU/WASM inference |
| Java |
java/ |
Cross-platform JVM |
| C++ |
cpp/ |
High-performance C++ |
| C# |
csharp/ |
.NET ecosystem |
| Go |
go/ |
Go implementation |
| Swift |
swift/ |
macOS applications |
| iOS |
ios/ |
Native iOS apps |
| Rust |
rust/ |
Memory-safe systems |
| Flutter |
flutter/ |
Cross-platform apps |
For detailed usage instructions, please refer to the README.md in each language directory.
Natural Text Handling
Supertonic is designed to handle complex, real-world text inputs that contain natural prose, punctuation, abbreviations, and proper nouns.
These historical audio samples are hosted externally and are not maintained as part of this archive.
Overview of Test Cases:
| Category |
Key Challenges |
Supertonic |
ElevenLabs |
OpenAI |
Gemini |
Microsoft |
| Financial Expression |
Decimal currency, abbreviated magnitudes (M, K), currency symbols, currency codes |
✅ |
❌ |
❌ |
❌ |
❌ |
| Phone Number |
Area codes, hyphens, extensions (ext.) |
✅ |
❌ |
❌ |
❌ |
❌ |
| Technical Unit |
Decimal numbers with units, abbreviated technical notations |
✅ |
❌ |
❌ |
❌ |
❌ |
Example 1: Financial Expression
Text:
"The startup secured $5.2M in venture capital, a huge leap from their initial $450K seed round."
Challenges:
- Decimal point in currency ($5.2M should be read as "five point two million")
- Abbreviated magnitude units (M for million, K for thousand)
- Currency symbol ($) that needs to be properly pronounced as "dollars"
Audio Samples:
Example 2: Phone Number
Text:
"You can reach the hotel front desk at (212) 555-0142 ext. 402 anytime."
Challenges:
- Area code in parentheses that should be read
Supertonic 是一个速度极快的本地文字转语音系统：它通过 ONNX Runtime 在本地把文字转换成 44.1kHz 16 位 WAV 语音——不用云端，不用调用 API，也不需要 GPU。开源权重的模型 Supertonic 3 支持 31 种语言。