---
title: fish-speech-1.5
canonical_url: "https://www.modelscope.cn/models/ModelsLab/fish-speech-1.5"
md_url: "https://www.modelscope.cn/models/ModelsLab/fish-speech-1.5.md"
repository: ModelsLab/fish-speech-1.5
last_updated: 2025-07-30
license: cc-by-nc-sa-4.0
pipeline_tag: text-to-speech
tasks:
  - text-to-speech
model_type:
  - dual_ar
library_name:
  - pytorch
frameworks:
  - pytorch
language:
  - zh
  - en
  - de
  - ja
  - fr
  - es
  - ko
  - ar
  - nl
  - ru
  - it
  - pl
  - pt
downloads: 252
stars: 0
tags:
  - text-to-speech
---

# fish-speech-1.5

> fish-speech-1.5 - ModelsLab 在 ModelScope 开源的模型。Fish Speech V1.5 is a leading text-to-speech (TTS) model trained on more than 1 million hours of audio data in multiple languages.

ModelsLab/fish-speech-1.5 是 ModelScope 魔搭社区上的text-to-speech模型，采用 cc-by-nc-sa-4.0 许可。

- **Repository**: ModelsLab/fish-speech-1.5
- **License**: cc-by-nc-sa-4.0
- **Tasks**: text-to-speech
- **Tags**: text-to-speech
- **Downloads**: 252
- **Stars**: 0
- **Last updated**: 2025-07-30

Source: https://www.modelscope.cn/models/ModelsLab/fish-speech-1.5

---

# Fish Speech V1.5

**Fish Speech V1.5** is a leading text-to-speech (TTS) model trained on more than 1 million hours of audio data in multiple languages.

Supported languages:
- English (en) >300k hours
- Chinese (zh) >300k hours
- Japanese (ja) >100k hours
- German (de) ~20k hours
- French (fr) ~20k hours
- Spanish (es) ~20k hours
- Korean (ko) ~20k hours
- Arabic (ar) ~20k hours
- Russian (ru) ~20k hours
- Dutch (nl) <10k hours
- Italian (it) <10k hours
- Polish (pl) <10k hours
- Portuguese (pt) <10k hours

Please refer to [Fish Speech Github](https://github.com/fishaudio/fish-speech) for more info.  
Demo available at [Fish Audio](https://fish.audio/).

## Citation

If you found this repository useful, please consider citing this work:

```
@misc{fish-speech-v1.4,
      title={Fish-Speech: Leveraging Large Language Models for Advanced Multilingual Text-to-Speech Synthesis}, 
      author={Shijia Liao and Yuxuan Wang and Tianyu Li and Yifan Cheng and Ruoyi Zhang and Rongzhi Zhou and Yijin Xing},
      year={2024},
      eprint={2411.01156},
      archivePrefix={arXiv},
      primaryClass={cs.SD},
      url={https://arxiv.org/abs/2411.01156}, 
}
```

## License

This model is permissively licensed under the BY-CC-NC-SA-4.0 license.