---
title: LEMAS-TTS
canonical_url: "https://www.modelscope.cn/models/LEMAS/LEMAS-TTS"
md_url: "https://www.modelscope.cn/models/LEMAS/LEMAS-TTS.md"
repository: LEMAS/LEMAS-TTS
last_updated: 2026-03-31
license: CC-BY-4.0
pipeline_tag: text-to-speech
tasks:
  - text-to-speech
parameters: 681.3M
tensor_type:
  - BOOL
  - F32
  - I64
library_name:
  - onnx
  - safetensors
  - pytorch
frameworks:
  - Pytorch
language:
  - it
  - pt
  - es
  - fr
  - de
  - vi
  - id
  - ru
  - en
  - zh
downloads: 40
stars: 0
tags:
  - zero-shot
  - multilingual
---

# LEMAS-TTS

> LEMAS-TTS - LEMAS 在 ModelScope 开源的模型。LEMAS-TTS is a multilingual zero-shot text-to-speech system, presented in the paper LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models.

LEMAS/LEMAS-TTS 是 ModelScope 魔搭社区上的 681.3M 参数text-to-speech模型，采用 CC-BY-4.0 许可。

- **Repository**: LEMAS/LEMAS-TTS
- **License**: CC-BY-4.0
- **Tasks**: text-to-speech
- **Parameters**: 681.3M
- **Tags**: zero-shot, multilingual
- **Downloads**: 40
- **Stars**: 0
- **Last updated**: 2026-03-31

Source: https://www.modelscope.cn/models/LEMAS/LEMAS-TTS

---

# LEMAS-TTS

LEMAS-TTS is a multilingual zero-shot text-to-speech system, presented in the paper [LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models](https://huggingface.co/papers/2601.04233).

- **Project Page:** [https://lemas-project.github.io/LEMAS-Project](https://lemas-project.github.io/LEMAS-Project)
- **Paper:** [https://arxiv.org/abs/2601.04233](https://arxiv.org/abs/2601.04233)
- **GitHub Repository:** [https://github.com/LEMAS-Project/LEMAS-TTS](https://github.com/LEMAS-Project/LEMAS-TTS)
- **Hugging Face Demo:** [https://huggingface.co/spaces/LEMAS-Project/LEMAS-TTS](https://huggingface.co/spaces/LEMAS-Project/LEMAS-TTS)

## Model Description

LEMAS-TTS is built upon a non-autoregressive flow-matching framework. It leverages the massive scale and linguistic diversity of the LEMAS-Dataset to achieve robust zero-shot multilingual synthesis. The model incorporates accent-adversarial training and CTC loss to mitigate cross-lingual accent issues, enhancing synthesis stability and quality across diverse languages.

## Supported Languages

The model supports 10 major languages for zero-shot synthesis:
- Chinese (zh)
- English (en)
- Spanish (es)
- Russian (ru)
- French (fr)
- German (de)
- Italian (it)
- Portuguese (pt)
- Indonesian (id)
- Vietnamese (vi)

## Training Data

LEMAS-TTS was trained on the [LEMAS-Dataset](https://huggingface.co/datasets/LEMAS-Project/LEMAS-Dataset-train), which is, to our knowledge, currently the largest open-source multilingual speech corpus with word-level timestamps. It covers over 150,000 hours across 10 major languages.

## Citation

```bibtex
@article{zhao2026lemas,
  title={LEMAS: A 150K-Hour Large-scale Extensible Multilingual Audio Suite with Generative Speech Models},
  author={Zhao, Zhiyuan and Lin, Lijian and Zhu, Ye and Xie, Kai and Liu, Yunfei and Li, Yu},
  journal={arXiv preprint arXiv:2601.04233},
  year={2026}
}
```