supertonic README

The project's README from github.com/supertone-oss-archive/supertonic. As one markdown file: README.md.

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 3 Banner

GitHub | Source Archive Models GitHub | Python Package Docs | Python PyPI

Supertonic | Trendshift

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

🌍 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.

1. Clone the source and install the download tool

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:

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

Performance Highlights

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

Supertonic 3 reading accuracy compared with measured model ranges and VoxCPM2

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

Supertonic 2 and Supertonic 3 comparison

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.

Runtime Footprint

Supertonic CPU runtime compared with GPU baselines

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

Model size comparison

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:

System Result Audio Sample
Supertonic ✅ 🎧 Play Audio
ElevenLabs Flash v2.5 ❌ 🎧 Play Audio
OpenAI TTS-1 ❌ 🎧 Play Audio
Gemini 2.5 Flash TTS ❌ 🎧 Play Audio
VibeVoice Realtime 0.5B ❌ 🎧 Play Audio
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 (supertone-oss-archive/supertonic)

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Что это такое?Supertonic — это очень быстрая система синтеза речи (text-to-speech), работающая прямо на устройстве: она локально превращает текст в речь в формате WAV 44,1 кГц, 16 бит, через ONNX Runtime — без облака, без API-запросов и без GPU. Модель с открытыми весами, Supertonic 3, поддерживает 31 язык.
Это приложение, которое я устанавливаю, или модель с SDK, которые я встраиваю в свой проект?Это модель с открытыми весами плюс SDK: компактный чекпоинт на 99 млн параметров с готовыми примерами для Python, Node.js, браузера (WebGPU/WASM), Java, C++, C#, Go, Swift, iOS, Rust и Flutter — вы встраиваете её в своё приложение.
Как запустить его у себя?Склонируйте репозиторий, настройте Python 3.11 в виртуальном окружении, скачайте архив с файлами модели (вход на Hugging Face не нужен), затем запустите пример — готовый WAV-файл появится в py/results/. Есть и pip-пакет supertonic.
Для SDK на других языках нужно что-то доустанавливать?Да — некоторым средам выполнения нужны нативные компоненты: Go требует библиотеку ONNX Runtime на C (brew install onnxruntime на macOS), Java — полноценный JDK, например openjdk@17, а C# рассчитан на .NET 9.
Проект ещё поддерживается?Нет — репозиторий заархивирован, разработка прекращена. Код и веса остаются доступны по своим лицензиям, но обновлений, исправлений ошибок и патчей безопасности не будет, а хостинговые демо и Voice Builder в архив не входят.
Может ли он синтезировать речь без интернета?Да — после скачивания файлов модели инференс полностью идёт локально. Демо для электронной книги работало в режиме полёта со средним RTF 0,3×.
Текст, который я синтезирую, куда-то отправляется с моего устройства?Нет — всё работает на вашем устройстве, без облака и API-запросов, поэтому ваш текст и сгенерированное аудио никогда не покидают компьютер.
Насколько он быстрый на самом деле?Быстрый по задумке: в README сказано, что целая веб-страница может превратиться в аудио меньше чем за секунду — это показано в демо с расширением для Chrome. На бенчмарке Minimax-MLS-test показатели WER/CER у Supertonic 3 остаются конкурентными по сравнению с куда более крупными открытыми TTS-системами вроде VoxCPM2, OmniVoice и Qwen3-TTS.
Могу я клонировать голос или придётся обходиться встроенными?Репозиторий с открытыми весами умеет только синтез с фиксированными голосами — официального пайплайна клонирования голоса в нём нет. Voice Builder умел превращать короткую референсную запись в файл кастомного голоса для Supertonic 2 и 3, но этот хостинговый сервис в архив не входит; клонирование «под ключ» доступно в Supertone Play и через Supertone API.
Можно поднять его как локальный API-сервер?Да — в Python-SDK есть supertonic serve: локальный HTTP-сервер с нативным эндпоинтом /v1/tts и эндпоинтом /v1/audio/speech, совместимым с OpenAI, так что существующие OpenAI TTS-клиенты могут указывать на вашу машину вместо облака.
В нём несколько голосов или всего один?Вместе с файлами модели поставляется несколько готовых голосовых стилей — шесть из них, M3-M5 и F3-F5, добавили в декабре 2025 года, — а также 10 встроенных тегов выразительности, которые добавляют речи естественных оттенков без prompt-инженерии и референсного аудио.
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