Fish Speech: Fast and Highly Accurate Cloning of English and Chinese Speech Using Few Samples

General Introduction

Fish Speech is an open source text-to-speech (TTS) synthesis tool developed by Fish Audio. The tool is based on cutting-edge AI technologies such as VQ-GAN, Llama, and VITS, and is capable of converting text into realistic speech.Fish Speech not only supports multiple languages, but also provides an efficient speech synthesis solution for a variety of application scenarios, such as voice-over, voice assistants, and accessible reading.

Experience it online at https://fish.audio/zh-CN/

Recommended 30-second audio

Function List

• Multi-language support: Supports text-to-speech conversion in multiple languages.
• Efficient synthesis: Efficient speech synthesis based on VQ-GAN, Llama and VITS.
• open source project: The code is open source and users can download and use it freely.
• Online Demo: Provide online demo function, users can directly experience the effect of speech synthesis.
• Model Download: Support for downloading pre-trained models from the Hugging Face platform.

Using Help

Installation process

system requirements

• GPU Memory: 4GB (for reasoning), 8GB (for fine-tuning)
• systems: Linux, Windows

Windows Configuration

professional user

• Consider using WSL2 or Docker to run the codebase.

non-professional user

1. Unzip the project zipThe
2. strike (on the keyboard) install_env.bat installation environmentThe
   • You can decide whether or not to use the mirror download by editing the USE_MIRROR entry in install_env.bat.
     • USE_MIRROR=false Use the original site to download the latest stable version of the torch environment.
     • USE_MIRROR=true Use the mirror site to download the latest torch environment (default).
   • You can decide whether to enable the compilable environment download by editing the INSTALL_TYPE entry of install_env.bat.
     • INSTALL_TYPE=preview Download the development version of the compilation environment.
     • INSTALL_TYPE=stable Download the stable version without the compilation environment.
3. If step 2 INSTALL_TYPE=previewIf you do not want to use this step, then perform this step (which can be skipped; this step activates the compilation modeling environment).
   • Download the LLVM compiler:
     • LLVM-17.0.6(Original site download)
     • LLVM-17.0.6(mirror site download)
   • After downloading LLVM-17.0.6-win64.exe, double-click it to install it, choose a suitable installation location, and check Add Path to Current User to add environment variables.
4. Download and install Microsoft Visual C++ Redistributable Packageto solve the potential .dll loss problem.
   • MSVC++ 14.40.33810.0 downloads
5. Download and install Visual Studio Community Editionto get the MSVC++ compilation tool to resolve LLVM header file dependencies.
   • Visual Studio Download
   • After installing the Visual Studio Installer, download Visual Studio Community 2022.
   • Click on the Modify button, find the Desktop Development using C++ item and check Download.
6. download and install CUDA Toolkit 12The
7. double-click start.bat Open the Training Reasoning WebUI administration interface. If necessary, modify API_FLAGS as indicated below.
   • Want to start the reasoning WebUI interface? Edit API_FLAGS.txt in the project root directory and change the first three lines to the following format:

     --infer
     # --api
     # --listen ...
     

   • Want to start the API server? Edit API_FLAGS.txt in the root directory of your project and change the first three lines to the following format:

     # --infer
     --api
     --listen ...
     

8. double-click run_cmd.bat Enter the conda/python command line environment for this projectThe

Linux Configuration

1. Create a python 3.10 virtual environmentYou can also use virtualenv:

   conda create -n fish-speech python=3.10
   conda activate fish-speech
   

2. Installing pytorch::

   pip3 install torch torchvision torchaudio
   

3. Install fish-speech::

   pip3 install -e . [stable]
   

4. (Ubuntu / Debian users) Install sox::

   apt install libsox-dev
   

Docker Configuration

1. Installing the NVIDIA Container Toolkit::
   • For Ubuntu users:

     curl -fsSL https://nvidia.github.io/libnvidia-container/gpgkey | sudo gpg --dearmor -o /usr/share/keyrings/nvidia-container-toolkit- keyring.gpg \
         && curl -s -L https://nvidia.github.io/libnvidia-container/stable/deb/nvidia-container-toolkit.list | \
             sed 's#deb https://#deb [signed-by=/usr/share/keyrings/nvidia-container-toolkit-keyring.gpg] https://#g' | \
             sudo tee /etc/apt/sources.list.d/nvidia-container-toolkit.list
     sudo apt-get update
     sudo apt-get install -y nvidia-container-toolkit
     sudo systemctl restart docker
     

   • For users with other Linux distributions, please refer to: NVIDIA Container Toolkit Install-guide for installation instructions.
2. Pull and run the fish-speech image::

   docker pull lengyue233/fish-speech
   docker run -it \
       --name fish-speech \
       --gpus all \
       --p 7860:7860 \
       lengyue233/fish-speech \
       zsh
   

   • If you need to use a different port, modify the -p parameters are YourPort:7860The
3. Download Model Dependencies::
   • Make sure you are in a terminal within the docker container before downloading the required vqgan and llama models from our huggingface repository:

     huggingface-cli download fishaudio/fish-speech-1.4 --local-dir checkpoints/fish-speech-1.4
     

   • For users in mainland China, it can be downloaded through the mirror site:

     HF_ENDPOINT=https://hf-mirror.com huggingface-cli download fishaudio/fish-speech-1.4 --local-dir checkpoints/fish-speech-1.4
     

4. To configure environment variables, access the WebUI::
   • In a terminal inside the docker container, type:

     export GRADIO_SERVER_NAME="0.0.0.0"
     

   • Next, in the terminal inside the docker container, type:

     python tools/webui.py
     

   • If WSL or MacOS, access the http://localhost:7860 The WebUI interface opens.
   • If deployed on a server, replace the localhost is your server IP.

Fish Audio One-Click Installer

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