fishaudio/fish-speechEnglish | 简体中文 | Portuguese | 日本語 | 한국어 | العربية
</a> <a target="_blank" href="[***]"> </a> <a target="_blank" href="[***]"> </a>
</a> <a target="_blank" href="[***]"> </a> <a target="_blank" href="[***]"> </a>
[!IMPORTANT] License Notice
This codebase is released under Apache License and all model weights are released under CC-BY-NC-SA-4.0 License. Please refer to LICENSE for more details.
[!WARNING] Legal Disclaimer
We do not hold any responsibility for any illegal usage of the codebase. Please refer to your local laws about DMCA and other related laws.
Here are the official documents for Fish Speech, follow the instructions to get started easily.
We are excited to announce that we have rebranded to OpenAudio — introducing a revolutionary new series of advanced Text-to-Speech models that builds upon the foundation of Fish-Speech.
We are proud to release OpenAudio-S1 as the first model in this series, delivering significant improvements in quality, performance, and capabilities.
OpenAudio-S1 comes in two versions: OpenAudio-S1 and OpenAudio-S1-mini. Both models are now available on Fish Audio Playground (for OpenAudio-S1) and Hugging Face (for OpenAudio-S1-mini).
Visit the OpenAudio website for blog & tech report.
We use Seed TTS Eval Metrics to evaluate the model performance, and the results show that OpenAudio S1 achieves 0.008 WER and 0.004 CER on English text, which is significantly better than previous models. (English, auto eval, based on OpenAI gpt-4o-transcribe, speaker distance using Revai/pyannote-wespeaker-voxceleb-resnet34-LM)
| Model | Word Error Rate (WER) | Character Error Rate (CER) | Speaker Distance |
|---|---|---|---|
| S1 | 0.008 | 0.004 | 0.332 |
| S1-mini | 0.011 | 0.005 | 0.380 |
OpenAudio S1 has achieved the #1 ranking on TTS-Arena2, the benchmark for text-to-speech evaluation:
OpenAudio S1 supports a variety of emotional, tone, and special markers to enhance speech synthesis:
(angry) (sad) (excited) (surprised) (satisfied) (delighted) (scared) (worried) (upset) (nervous) (frustrated) (depressed) (empathetic) (embarrassed) (disgusted) (moved) (proud) (relaxed) (grateful) (confident) (interested) (curious) (confused) (joyful)
(disdainful) (unhappy) (anxious) (hysterical) (indifferent) (impatient) (guilty) (scornful) (panicked) (furious) (reluctant) (keen) (disapproving) (negative) (denying) (astonished) (serious) (sarcastic) (conciliative) (comforting) (sincere) (sneering) (hesitating) (yielding) (painful) (awkward) (amused)
(in a hurry tone) (shouting) (screaming) (whispering) (soft tone)
(laughing) (chuckling) (sobbing) (crying loudly) (sighing) (panting) (groaning) (crowd laughing) (background laughter) (audience laughing)
You can also use Ha,ha,ha to control, there's many other cases waiting to be explored by yourself.
(Support for English, Chinese and Japanese now, and more languages is coming soon!)
| Model | Size | Availability | Features |
|---|---|---|---|
| S1 | 4B parameters | Avaliable on fish.audio | Full-featured flagship model |
| S1-mini | 0.5B parameters | Avaliable on huggingface hf space | Distilled version with core capabilities |
Both S1 and S1-mini incorporate online Reinforcement Learning from Human Feedback (RLHF).
Zero-shot & Few-shot TTS: Input a 10 to 30-second vocal sample to generate high-quality TTS output. For detailed guidelines, see Voice Cloning Best Practices.
Multilingual & Cross-lingual Support: Simply copy and paste multilingual text into the input box—no need to worry about the language. Currently supports English, Japanese, Korean, Chinese, French, German, Arabic, and Spanish.
No Phoneme Dependency: The model has strong generalization capabilities and does not rely on phonemes for TTS. It can handle text in any language script.
Highly Accurate: Achieves a low CER (Character Error Rate) of around 0.4% and WER (Word Error Rate) of around 0.8% for Seed-TTS Eval.
Fast: Accelerated by torch compile, the real-time factor is approximately 1:7 on an Nvidia RTX 4090 GPU.
WebUI Inference: Features an easy-to-use, Gradio-based web UI compatible with Chrome, Firefox, Edge, and other browsers.
GUI Inference: Offers a PyQt6 graphical interface that works seamlessly with the API server. Supports Linux, Windows, and macOS. See GUI.
Deploy-Friendly: Easily set up an inference server with native support for Linux, Windows (MacOS comming soon), minimizing speed loss.
bibtex@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={[***]}, }
探索更多轩辕镜像的使用方法,找到最适合您系统的配置方式
通过 Docker 登录认证访问私有仓库
在 Linux 系统配置镜像服务
在 Docker Desktop 配置镜像
Docker Compose 项目配置
Kubernetes 集群配置 Containerd
K3s 轻量级 Kubernetes 镜像加速
在宝塔面板一键配置镜像
Synology 群晖 NAS 配置
飞牛 fnOS 系统配置镜像
极空间 NAS 系统配置服务
爱快 iKuai 路由系统配置
绿联 NAS 系统配置镜像
QNAP 威联通 NAS 配置
Podman 容器引擎配置
HPC 科学计算容器配置
ghcr、Quay、nvcr 等镜像仓库
无需登录使用专属域名
需要其他帮助?请查看我们的 常见问题Docker 镜像访问常见问题解答 或 提交工单
免费版仅支持 Docker Hub 访问,不承诺可用性和速度;专业版支持更多镜像源,保证可用性和稳定速度,提供优先客服响应。
专业版支持 docker.io、gcr.io、ghcr.io、registry.k8s.io、nvcr.io、quay.io、mcr.microsoft.com、docker.elastic.co 等;免费版仅支持 docker.io。
当返回 402 Payment Required 错误时,表示流量已耗尽,需要充值流量包以恢复服务。
通常由 Docker 版本过低导致,需要升级到 20.x 或更高版本以支持 V2 协议。
先检查 Docker 版本,版本过低则升级;版本正常则验证镜像信息是否正确。
使用 docker tag 命令为镜像打上新标签,去掉域名前缀,使镜像名称更简洁。
来自真实用户的反馈,见证轩辕镜像的优质服务