# Supertonic — Lightning Fast, On-Device, Accurate TTS

[![v3 Demo](https://img.shields.io/badge/🤗%20v3-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic-3)
[![v3 Models](https://img.shields.io/badge/🤗%20v3-Models-blue)](https://huggingface.co/Supertone/supertonic-3)
[![v2 Branch](https://img.shields.io/badge/v2-release%2Fsupertonic--2-lightgrey)](https://github.com/supertone-inc/supertonic/tree/release/supertonic-2)
[![v1 Demo](https://img.shields.io/badge/🤗%20v1%20(old)-Demo-lightgrey)](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo)
[![v1 Models](https://img.shields.io/badge/🤗%20v1%20(old)-Models-lightgrey)](https://huggingface.co/Supertone/supertonic)

<p align="center">
  <img src="img/Supertonic3_HeroImage.png" alt="Supertonic 3 Banner">
</p>

**Supertonic** is a lightning-fast, on-device 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.

### 📰 Update News

- **2026.04.29** - 🎉 **Supertonic 3** released with **31-language support**, improved reading accuracy, fewer repeat/skip failures, and v2-compatible public ONNX assets. [Demo](https://huggingface.co/spaces/Supertone/supertonic-3) | [Models](https://huggingface.co/Supertone/supertonic-3)
- **2026.01.22** - **[Voice Builder](https://supertonic.supertone.ai/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`](https://github.com/supertone-inc/supertonic/tree/release/supertonic-2) branch.
- **2025.12.10** - Added `supertonic` PyPI package! Install via `pip install supertonic`. For details, visit [supertonic-py documentation](https://supertone-inc.github.io/supertonic-py)
- **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
- **2025.12.08** - Optimized ONNX models via [OnnxSlim](https://github.com/inisis/OnnxSlim) now available on [Hugging Face Models](https://huggingface.co/Supertone/supertonic)
- **2025.11.24** - Added Flutter SDK support with macOS compatibility

## Quick Start

Install the Python SDK and generate speech immediately. On the first run, Supertonic downloads the model assets from Hugging Face automatically.

```bash
pip install supertonic
```

### Python

```python
from supertonic import TTS

# First run downloads the model from Hugging Face automatically.
tts = TTS(auto_download=True)

style = tts.get_voice_style(voice_name="M1")

text = "A gentle breeze moved through the open window while everyone listened to the story."
wav, duration = tts.synthesize(text, voice_style=style, lang="en")

tts.save_audio(wav, "output.wav")
print(f"Generated {duration:.2f}s of audio")
```

## Getting Started

First, clone the repository:

```bash
git clone https://github.com/supertone-inc/supertonic.git
cd supertonic
```

### Prerequisites

Before running the examples, download the ONNX models and preset voices, and place them in the `assets` directory:

> **Note:** The Hugging Face repository uses Git LFS. Please ensure Git LFS is installed and initialized before cloning or pulling large model files.
> - macOS: `brew install git-lfs && git lfs install`
> - Generic: see `https://git-lfs.com` for installers

```bash
git lfs install
git clone https://huggingface.co/Supertone/supertonic-3 assets
```

Some language examples need native runtimes:
- **Go**: install the ONNX Runtime C library. On macOS, `brew install onnxruntime` is enough; the Go example auto-detects Homebrew paths.
- **Java**: use a JDK, not just a JRE. On macOS, `brew install openjdk@17` works.
- **C#**: targets .NET 9 and allows major-version roll-forward, so .NET 9 or newer runtimes can run it.

Then run the Python example:

```bash
cd py
uv sync
uv run example_onnx.py
```

This generates `outputs/output.wav` using the default preset voice.

### Other Runtime Examples

<details>
<summary><b>Run Supertonic in other languages and platforms</b></summary>

**Node.js Example** ([Details](nodejs/))
```bash
cd nodejs
npm install
npm start
```

**Browser Example** ([Details](web/))
```bash
cd web
npm install
npm run dev
```

**Java Example** ([Details](java/))
```bash
cd java
mvn clean install
mvn exec:java
```

**C++ Example** ([Details](cpp/))
```bash
cd cpp
mkdir build && cd build
cmake .. && cmake --build . --config Release
./example_onnx
```

**C# Example** ([Details](csharp/))
```bash
cd csharp
dotnet restore
dotnet run
```

**Go Example** ([Details](go/))
```bash
cd go
go mod download
go run example_onnx.go helper.go
```

**Swift Example** ([Details](swift/))
```bash
cd swift
swift build -c release
.build/release/example_onnx
```

**Rust Example** ([Details](rust/))
```bash
cd rust
cargo build --release
./target/release/example_onnx
```

**iOS Example** ([Details](ios/))
```bash
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.

</details>


### 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 16-bit WAV files

## 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

<p align="center">
  <img src="img/metrics/s3_vs_measured_wer_range_voxcpm2.png" alt="Supertonic 3 reading accuracy compared with measured model ranges and VoxCPM2">
</p>

Across measured languages, 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.

### Supertonic 2 to Supertonic 3

<p align="center">
  <img src="img/metrics/supertonic2_vs_3_comparison.png" alt="Supertonic 2 and Supertonic 3 comparison">
</p>

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

<p align="center">
  <img src="img/metrics/runtime_cpu_gpu_latency_memory.png" alt="Supertonic CPU runtime compared with GPU baselines">
</p>

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

<p align="center">
  <img src="img/metrics/model_size_comparison.png" alt="Model size comparison">
</p>

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.

## Demo

> **Try it now**: Experience Supertonic in your browser with our [**Interactive Demo**](https://huggingface.co/spaces/Supertone/supertonic-3), or get started with pre-trained models from [**Hugging Face Hub**](https://huggingface.co/Supertone/supertonic-3)

### 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

## Why Supertonic?

- **Blazingly Fast**: Optimized for low-latency, on-device speech generation across desktop, browser, and edge deployments
- **Lightweight**: Compact ONNX assets designed for efficient local execution
- **On-Device Capable**: Complete privacy and zero network dependency
- **Accurate Reading**: Improved reading stability with fewer repeat and skip failures
- **Expressive Tags**: Supports simple expression tags such as `<laugh>`, `<breath>`, and `<sigh>`
- **Flexible Deployment**: Ready-to-use examples across Python, JavaScript, browser, mobile, and native runtimes

## Language Support

Supertonic 3 supports 31 languages:

| Code | Language | Code | Language | Code | Language | Code | Language |
|------|----------|------|----------|------|----------|------|----------|
| `en` | English | `ko` | Korean | `ja` | Japanese | `ar` | Arabic |
| `bg` | Bulgarian | `cs` | Czech | `da` | Danish | `de` | German |
| `el` | Greek | `es` | Spanish | `et` | Estonian | `fi` | Finnish |
| `fr` | French | `hi` | Hindi | `hr` | Croatian | `hu` | Hungarian |
| `id` | Indonesian | `it` | Italian | `lt` | Lithuanian | `lv` | Latvian |
| `nl` | Dutch | `pl` | Polish | `pt` | Portuguese | `ro` | Romanian |
| `ru` | Russian | `sk` | Slovak | `sl` | Slovenian | `sv` | Swedish |
| `tr` | Turkish | `uk` | Ukrainian | `vi` | Vietnamese | | |

We provide ready-to-use TTS inference examples across multiple ecosystems:

| Language/Platform | Path | Description |
|-------------------|------|-------------|
| [**Python**](py/) | `py/` | ONNX Runtime inference |
| [**Node.js**](nodejs/) | `nodejs/` | Server-side JavaScript |
| [**Browser**](web/) | `web/` | WebGPU/WASM inference |
| [**Java**](java/) | `java/` | Cross-platform JVM |
| [**C++**](cpp/) | `cpp/` | High-performance C++ |
| [**C#**](csharp/) | `csharp/` | .NET ecosystem |
| [**Go**](go/) | `go/` | Go implementation |
| [**Swift**](swift/) | `swift/` | macOS applications |
| [**iOS**](ios/) | `ios/` | Native iOS apps |
| [**Rust**](rust/) | `rust/` | Memory-safe systems |
| [**Flutter**](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.

> 🎧 **View audio samples more easily**: Check out our [**Interactive Demo**](https://huggingface.co/spaces/Supertone/supertonic-3) for a better viewing experience of all audio examples

**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 | ✅ | ❌ | ❌ | ❌ | ❌ |

<details>
<summary><b>Example 1: Financial Expression</b></summary>

<br>

**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](https://drive.google.com/file/d/1eancUOhiSXCVoTu9ddh4S-OcVQaWrPV-/view?usp=sharing) |
| ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1-r2scv7XQ1crIDu6QOh3eqVl445W6ap_/view?usp=sharing) |
| OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1MFDXMjfmsAVOqwPx7iveS0KUJtZvcwxB/view?usp=sharing) |
| Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1dEHpNzfMUucFTJPQK0k4RcFZvPwQTt09/view?usp=sharing) |
| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1b69XWBQnSZZ0WZeR3avv7E8mSdoN6p6P/view?usp=sharing) |

</details>

<details>
<summary><b>Example 2: Phone Number</b></summary>

<br>

**Text:**
> "You can reach the hotel front desk at **(212) 555-0142 ext. 402** anytime."

**Challenges:**
- Area code in parentheses that should be read as separate digits
- Phone number with hyphen separator (555-0142)
- Abbreviated extension notation (ext.)
- Extension number (402)

**Audio Samples:**

| System | Result | Audio Sample |
|--------|--------|--------------|
| **Supertonic** | ✅ | [🎧 Play Audio](https://drive.google.com/file/d/1z-e5iTsihryMR8ll1-N1YXkB2CIJYJ6F/view?usp=sharing) |
| ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1HAzVXFTZfZm0VEK2laSpsMTxzufcuaxA/view?usp=sharing) |
| OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/15tjfAmb3GbjP_kmvD7zSdIWkhtAaCPOg/view?usp=sharing) |
| Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1BCL8n7yligUZyso970ud7Gf5NWb1OhKD/view?usp=sharing) |
| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1c0c0YM_Qm7XxSk2uSVYLbITgEDTqaVzL/view?usp=sharing) |

</details>

<details>
<summary><b>Example 3: Technical Unit</b></summary>

<br>

**Text:**
> "Our drone battery lasts **2.3h** when flying at **30kph** with full camera payload."

**Challenges:**
- Decimal time duration with abbreviation (2.3h = two point three hours)
- Speed unit with abbreviation (30kph = thirty kilometers per hour)
- Technical abbreviations (h for hours, kph for kilometers per hour)
- Technical/engineering context requiring proper pronunciation

**Audio Samples:**

| System | Result | Audio Sample |
|--------|--------|--------------|
| **Supertonic** | ✅ | [🎧 Play Audio](https://drive.google.com/file/d/1kvOBvswFkLfmr8hGplH0V2XiMxy1shYf/view?usp=sharing) |
| ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1_SzfjWJe5YEd0t3R7DztkYhHcI_av48p/view?usp=sharing) |
| OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1P5BSilj5xFPTV2Xz6yW5jitKZohO9o-6/view?usp=sharing) |
| Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1GU82SnWC50OvC8CZNjhxvNZFKQb7I9_Y/view?usp=sharing) |
| VibeVoice Realtime 0.5B | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1lUTrxrAQy_viEK2Hlu3KLLtTCe8jvbdV/view?usp=sharing) |

</details>

> **Note:** These samples demonstrate how each system handles text normalization and pronunciation of complex expressions **without requiring pre-processing or phonetic annotations**.

## Built with Supertonic

| Project | Description | Links |
|---------|-------------|-------|
| **TLDRL** | Free, on-device TTS extension for reading any webpage | [Chrome](https://chromewebstore.google.com/detail/tldrl-lightning-tts-power/mdbiaajonlkomihpcaffhkagodbcgbme) |
| **Read Aloud** | Open-source TTS browser extension | [Chrome](https://chromewebstore.google.com/detail/read-aloud-a-text-to-spee/hdhinadidafjejdhmfkjgnolgimiaplp) · [Edge](https://microsoftedge.microsoft.com/addons/detail/read-aloud-a-text-to-spe/pnfonnnmfjnpfgagnklfaccicnnjcdkm) · [GitHub](https://github.com/ken107/read-aloud) |
| **PageEcho** | E-Book reader app for iOS | [App Store](https://apps.apple.com/us/app/pageecho/id6755965837) |
| **VoiceChat** | On-device voice-to-voice LLM chatbot in the browser | [Demo](https://huggingface.co/spaces/RickRossTN/ai-voice-chat) · [GitHub](https://github.com/irelate-ai/voice-chat) |
| **OmniAvatar** | Talking avatar video generator from photo + speech | [Demo](https://huggingface.co/spaces/alexnasa/OmniAvatar) |
| **CopiloTTS** | Kotlin Multiplatform TTS SDK via ONNX Runtime | [GitHub](https://github.com/sigmadeltasoftware/CopiloTTS) |
| **Voice Mixer** | PyQt5 tool for mixing and modifying voice styles | [GitHub](https://github.com/Topping1/Supertonic-Voice-Mixer) |
| **Supertonic MNN** | Lightweight library based on MNN (fp32/fp16/int8) | [GitHub](https://github.com/vra/supertonic-mnn) · [PyPI](https://pypi.org/project/supertonic-mnn/) |
| **Transformers.js** | Hugging Face's JS library with Supertonic support | [GitHub PR](https://github.com/huggingface/transformers.js/pull/1459) · [Demo](https://huggingface.co/spaces/webml-community/Supertonic-TTS-WebGPU) |
| **Pinokio** | 1-click localhost cloud for Mac, Windows, and Linux | [Pinokio](https://pinokio.co/) · [GitHub](https://github.com/SUP3RMASS1VE/SuperTonic-TTS) |

## Citation

The following papers describe the core technologies used in Supertonic. If you use this system in your research or find these techniques useful, please consider citing the relevant papers:

### SupertonicTTS: Main Architecture

This paper introduces the overall architecture of SupertonicTTS, including the speech autoencoder, flow-matching based text-to-latent module, and efficient design choices.

```bibtex
@article{kim2025supertonic,
  title={SupertonicTTS: Towards Highly Efficient and Streamlined Text-to-Speech System},
  author={Kim, Hyeongju and Yang, Jinhyeok and Yu, Yechan and Ji, Seunghun and Morton, Jacob and Bous, Frederik and Byun, Joon and Lee, Juheon},
  journal={arXiv preprint arXiv:2503.23108},
  year={2025},
  url={https://arxiv.org/abs/2503.23108}
}
```

### Length-Aware RoPE: Text-Speech Alignment

This paper presents Length-Aware Rotary Position Embedding (LARoPE), which improves text-speech alignment in cross-attention mechanisms.

```bibtex
@article{kim2025larope,
  title={Length-Aware Rotary Position Embedding for Text-Speech Alignment},
  author={Kim, Hyeongju and Lee, Juheon and Yang, Jinhyeok and Morton, Jacob},
  journal={arXiv preprint arXiv:2509.11084},
  year={2025},
  url={https://arxiv.org/abs/2509.11084}
}
```

### Self-Purifying Flow Matching: Training with Noisy Labels

This paper describes the self-purification technique for training flow matching models robustly with noisy or unreliable labels.

```bibtex
@article{kim2025spfm,
  title={Training Flow Matching Models with Reliable Labels via Self-Purification},
  author={Kim, Hyeongju and Yu, Yechan and Yi, June Young and Lee, Juheon},
  journal={arXiv preprint arXiv:2509.19091},
  year={2025},
  url={https://arxiv.org/abs/2509.19091}
}
```

## License

This project's sample code is released under the MIT License. - see the [LICENSE](https://github.com/supertone-inc/supertonic?tab=MIT-1-ov-file) for details.

The accompanying model is released under the OpenRAIL-M License. - see the [LICENSE](https://huggingface.co/Supertone/supertonic-3/blob/main/LICENSE) file for details.

This model was trained using PyTorch, which is licensed under the BSD 3-Clause License but is not redistributed with this project. - see the [LICENSE](https://docs.pytorch.org/FBGEMM/general/License.html) for details.

Copyright (c) 2026 Supertone Inc.