You can deploy this model and start earning money today!

alekshandru/
supertonic-3

Name: supertonic-3
Availability: InStock

Views

No views yet

Supertonic 3 | Lightning Fast, On-Device, Accurate TTS

Code

Python SDK

Supertonic is a lightweight text-to-speech system for local inference. It runs with ONNX Runtime entirely on your device, with no cloud call required for synthesis.

Supertonic 3 expands the open-weight release from 5 to 31 languages, improves reading stability, and reduces repeat/skip failures.

Quick Start

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

pip install supertonic

python

from supertonic import TTS

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")

What's New in Supertonic 3

31 languages: expanded from the 5-language Supertonic 2 release.
More stable reading: fewer repeat and skip failures, especially on short and long utterances.
Higher speaker similarity: improved similarity across the shared-language set compared with Supertonic 2.
Expression tags: supports simple tags such as <laugh>, <breath>, and <sigh>.

Custom Voices and Audio Samples

The open-weight package includes fixed preset voice styles for immediate local inference. If you want to hear how Supertonic 3 performs with zero-shot custom voice styles, visit the Audio Sample Demo to compare reference audio and generated speech across several use cases. To create your own Supertonic 3 voice-style JSON from reference audio, use Supertonic Voice Builder; purchased Voice Builder styles include downloadable embeddings for both Supertonic 2 and Supertonic 3.

Here are a few reference/generated pairs from the audio sample demo:

Call center, English
Text: Good morning, thank you for calling. How can I help you today?

Reference voice	Supertonic 3 output

Character voice, Japanese
Text: ふふっ、退屈してたところなの。ちょうどいい遊び相手、見つけたかも♪

Reference voice	Supertonic 3 output

Elder character voice, Korean
Text: 혼자 떠나기엔 길이 험하구나. 이 낡은 검을 가져가거라. 언젠가 어둠이 네 이름을 부르더라도, 부디 빛을 잊지 말거라.

Reference voice	Supertonic 3 output

Audiobook, English
Text: I was not afraid of silence. I had lived with it long enough to know that, sometimes, it speaks more honestly than people do.

Reference voice	Supertonic 3 output

Audiobook, Japanese
Text: その朝、ロンドンの霧はいつになく低く垂れこめていた。私はただの訪問者だと思っていたが、ホームズの目はすでに別の結論にたどり着いていた。

Reference voice	Supertonic 3 output

News, English
Text: Here’s a story worth paying attention to. Supertone has released Supertonic 3, its on-device TTS model. This version expands support to thirty-one languages and improves reading stability.

Reference voice	Supertonic 3 output

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

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

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.

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. It 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.

Supported 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

License

This project's sample code is released under the MIT License. See the GitHub repository for details.

The accompanying model is released under the OpenRAIL-M License. See the LICENSE file in this repository 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 PyTorch license for details.

alekshandru/supertonic-3