https://github.com/supertone-inc/supertonic

Lightning-fast, on-device TTS — running natively via ONNX.
https://github.com/supertone-inc/supertonic
cpp csharp go ios java lightweight nodejs on-device python rust swift text-to-speech tt tts web
Last synced: 7 months ago
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Lightning-fast, on-device TTS — running natively via ONNX.
Host: GitHub
URL: https://github.com/supertone-inc/supertonic
Owner: supertone-inc
License: mit
Created: 2025-11-18T08:23:58.000Z (7 months ago)
Default Branch: main
Last Pushed: 2025-11-18T11:15:05.000Z (7 months ago)
Last Synced: 2025-11-18T13:19:41.824Z (7 months ago)
Topics: cpp, csharp, go, ios, java, lightweight, nodejs, on-device, python, rust, swift, text-to-speech, tt, tts, web
Language: JavaScript
Homepage: https://huggingface.co/spaces/Supertone/supertonic
Size: 275 KB
Stars: 15
Watchers: 0
Forks: 1
Open Issues: 1
Metadata Files:
- Readme: README.md
- License: LICENSE
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README

          # Supertonic — Lightning Fast, On-Device TTS

[![Demo](https://img.shields.io/badge/🤗%20Hugging%20Face-Demo-yellow)](https://huggingface.co/spaces/Supertone/supertonic#interactive-demo)

[![Models](https://img.shields.io/badge/🤗%20Hugging%20Face-Models-blue)](https://huggingface.co/Supertone/supertonic)



  



**Supertonic** is a lightning-fast, on-device text-to-speech system designed for **extreme performance** with minimal computational overhead. Powered by ONNX Runtime, it runs entirely on your device—no cloud, no API calls, no privacy concerns.

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

### Table of Contents

- [Why Supertonic?](#why-supertonic)

- [See it in Action](#see-it-in-action)

- [Language Support](#language-support)

- [Getting Started](#getting-started)

- [Performance](#performance)

- [Citation](#citation)

- [License](#license)

## Why Supertonic?

- **⚡ Blazingly Fast**: Generates speech up to **167× faster than real-time** on consumer hardware (M4 Pro)—unmatched by any other TTS system

- **🪶 Ultra Lightweight**: Only **66M parameters**, optimized for efficient on-device performance with minimal footprint

- **📱 On-Device Capable**: **Complete privacy** and **zero latency**—all processing happens locally on your device

- **🎨 Natural Text Handling**: Seamlessly processes numbers, dates, currency, abbreviations, and complex expressions without pre-processing

- **⚙️ Highly Configurable**: Adjust inference steps, batch processing, and other parameters to match your specific needs

- **🧩 Flexible Deployment**: Deploy seamlessly across servers, browsers, and edge devices with multiple runtime backends.

## See it in Action

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

## Language Support

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 |

> For detailed usage instructions, please refer to the README.md in each language directory.

## 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 clone https://huggingface.co/Supertone/supertonic assets

```

### Quick Start

**Python Example** ([Details](py/))

```bash

cd py

uv sync

uv run example_onnx.py

```

**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

- Choose your iPhone as run destination → Build & Run

### Technical Details

- **Runtime**: ONNX Runtime for cross-platform inference (CPU-optimized; GPU mode is not tested)

- **Browser Support**: onnxruntime-web for client-side inference

- **Batch Processing**: Supports batch inference for improved throughput

- **Audio Output**: Outputs 16-bit WAV files

## Performance

We evaluated Supertonic's performance (with 2 inference steps) using two key metrics across input texts of varying lengths: Short (59 chars), Mid (152 chars), and Long (266 chars).

**Metrics:**

- **Characters per Second**: Measures throughput by dividing the number of input characters by the time required to generate audio. Higher is better.

- **Real-time Factor (RTF)**: Measures the time taken to synthesize audio relative to its duration. Lower is better (e.g., RTF of 0.1 means it takes 0.1 seconds to generate one second of audio).

### Characters per Second

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |

|--------|-----------------|----------------|-----------------|

| **Supertonic** (M4 pro - CPU) | 912 | 1048 | 1263 |

| **Supertonic** (M4 pro - WebGPU) | 996 | 1801 | 2509 |

| **Supertonic** (RTX4090) | 2615 | 6548 | 12164 |

| `API` [ElevenLabs Flash v2.5](https://elevenlabs.io/docs/api-reference/text-to-speech/convert) | 144 | 209 | 287 |

| `API` [OpenAI TTS-1](https://platform.openai.com/docs/guides/text-to-speech) | 37 | 55 | 82 |

| `API` [Gemini 2.5 Flash TTS](https://ai.google.dev/gemini-api/docs/speech-generation) | 12 | 18 | 24 |

| `API` [Supertone Sona speech 1](https://docs.supertoneapi.com/en/api-reference/endpoints/text-to-speech) | 38 | 64 | 92 |

| `Open` [Kokoro](https://github.com/hexgrad/kokoro/) | 104 | 107 | 117 |

| `Open` [NeuTTS Air](https://github.com/neuphonic/neutts-air) | 37 | 42 | 47 |

> **Notes:**  

> `API` = Cloud-based API services (measured from Seoul)  

> `Open` = Open-source models  

> Supertonic (M4 pro - CPU) and (M4 pro - WebGPU): Tested with ONNX  

> Supertonic (RTX4090): Tested with PyTorch model  

> Kokoro: Tested on M4 Pro CPU with ONNX  

> NeuTTS Air: Tested on M4 Pro CPU with Q8-GGUF

### Real-time Factor

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |

|--------|-----------------|----------------|-----------------|

| **Supertonic** (M4 pro - CPU) | 0.015 | 0.013 | 0.012 |

| **Supertonic** (M4 pro - WebGPU) | 0.014 | 0.007 | 0.006 |

| **Supertonic** (RTX4090) | 0.005 | 0.002 | 0.001 |

| `API` [ElevenLabs Flash v2.5](https://elevenlabs.io/docs/api-reference/text-to-speech/convert) | 0.133 | 0.077 | 0.057 |

| `API` [OpenAI TTS-1](https://platform.openai.com/docs/guides/text-to-speech) | 0.471 | 0.302 | 0.201 |

| `API` [Gemini 2.5 Flash TTS](https://ai.google.dev/gemini-api/docs/speech-generation) | 1.060 | 0.673 | 0.541 |

| `API` [Supertone Sona speech 1](https://docs.supertoneapi.com/en/api-reference/endpoints/text-to-speech) | 0.372 | 0.206 | 0.163 |

| `Open` [Kokoro](https://github.com/hexgrad/kokoro/) | 0.144 | 0.124 | 0.126 |

| `Open` [NeuTTS Air](https://github.com/neuphonic/neutts-air) | 0.390 | 0.338 | 0.343 |

Additional Performance Data (5-step inference)




**Characters per Second (5-step)**

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |

|--------|-----------------|----------------|-----------------|

| **Supertonic** (M4 pro - CPU) | 596 | 691 | 850 |

| **Supertonic** (M4 pro - WebGPU) | 570 | 1118 | 1546 |

| **Supertonic** (RTX4090) | 1286 | 3757 | 6242 |

**Real-time Factor (5-step)**

| System | Short (59 chars) | Mid (152 chars) | Long (266 chars) |

|--------|-----------------|----------------|-----------------|

| **Supertonic** (M4 pro - CPU) | 0.023 | 0.019 | 0.018 |

| **Supertonic** (M4 pro - WebGPU) | 0.024 | 0.012 | 0.010 |

| **Supertonic** (RTX4090) | 0.011 | 0.004 | 0.002 |

### Natural Text Handling

Supertonic is designed to handle complex, real-world text inputs that contain numbers, currency symbols, abbreviations, dates, and proper nouns.

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

**Overview of Test Cases:**

| Category | Key Challenges | Supertonic | ElevenLabs | OpenAI | Gemini |

|:--------:|:--------------:|:----------:|:----------:|:------:|:------:|

| Financial Expression | Decimal currency, abbreviated magnitudes (M, K), currency symbols, currency codes | ✅ | ❌ | ❌ | ❌ |

| Time and Date | Time notation, abbreviated weekdays/months, date formats | ✅ | ❌ | ❌ | ❌ |

| 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](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) |

Example 2: Time and Date




**Text:**

> "The train delay was announced at **4:45 PM** on **Wed, Apr 3, 2024** due to track maintenance."

**Challenges:**

- Time expression with PM notation (4:45 PM)

- Abbreviated weekday (Wed)

- Abbreviated month (Apr)

- Full date format (Apr 3, 2024)

**Audio Samples:**

| System | Result | Audio Sample |

|--------|--------|--------------|

| **Supertonic** | ✅ | [🎧 Play Audio](https://drive.google.com/file/d/1ehkZU8eiizBenG2DgR5tzBGQBvHS0Uaj/view?usp=sharing) |

| ElevenLabs Flash v2.5 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1ta3r6jFyebmA-sT44l8EaEQcMLVmuOEr/view?usp=sharing) |

| OpenAI TTS-1 | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1sskmem9AzHAQ3Hv8DRSZoqX_pye-CXuU/view?usp=sharing) |

| Gemini 2.5 Flash TTS | ❌ | [🎧 Play Audio](https://drive.google.com/file/d/1zx9X8oMsLMXW0Zx_SURoqjju-By2yh_n/view?usp=sharing) |

Example 3: 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 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) |

Example 4: Technical Unit




**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) |

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

## 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/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) 2025 Supertone Inc.
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