GitHub

Fish Speech

What is the project about?

Fish Speech is an open-source, multilingual text-to-speech (TTS) system that also offers voice cloning capabilities. It's designed to generate high-quality, natural-sounding speech from text in multiple languages. It also includes "Fish Agent", an end-to-end conversational AI.

What problem does it solve?

  • Provides a high-quality, multilingual TTS solution that doesn't require extensive voice samples for training (zero-shot and few-shot learning).
  • Simplifies multilingual TTS by automatically handling different languages without needing to specify them.
  • Eliminates the dependency on phonemes, allowing it to work with text in any language script.
  • Reduces errors in speech generation, achieving low CER and WER.
  • Offers fast inference speeds.
  • Provides an easy to deploy and use TTS system.
  • Fish Agent solves the problem of needing separate ASR, LLM, and TTS models by combining them.

What are the features of the project?

  • Zero-shot & Few-shot TTS: Generates speech from minimal voice samples (10-30 seconds).
  • Multilingual & Cross-lingual Support: Handles multiple languages (English, Japanese, Korean, Chinese, French, German, Arabic, Spanish) seamlessly.
  • No Phoneme Dependency: Works with text in any language script.
  • High Accuracy: Low Character Error Rate (CER) and Word Error Rate (WER).
  • Fast Inference: Optimized for speed, with good real-time factors on various GPUs.
  • WebUI & GUI Inference: Offers both web-based (Gradio) and desktop (PyQt6) interfaces.
  • Deploy-Friendly: Easy to set up an inference server.
  • Fish Agent Features:
    • End-to-End: Integrates ASR and TTS.
    • Timbre Control: Allows controlling voice timbre with reference audio.
    • Emotional Speech: Can generate speech with emotion.

What are the technologies used in the project?

  • Likely deep learning models, building upon architectures like VITS2, Bert-VITS2, GPT-VITS, and GPT-SoVITS.
  • Gradio (for the WebUI).
  • PyQt6 (for the GUI).
  • Docker (for deployment).
  • Python (implied by the provided links and context).
  • Large Language Models (mentioned in the tech report bibtex).

What are the benefits of the project?

  • Accessibility: Makes high-quality TTS accessible to a wider range of users and developers.
  • Flexibility: Supports multiple languages and voice cloning with minimal data.
  • Ease of Use: Provides user-friendly interfaces for both interaction and deployment.
  • Performance: Offers fast and accurate speech generation.
  • Open Source: Allows for community contributions and customization (Apache License for codebase, CC-BY-NC-SA-4.0 for model weights).
  • End-to-end solution: Fish Agent simplifies conversational AI development.

What are the use cases of the project?

  • Voice Cloning: Creating personalized voices for various applications.
  • Multilingual Content Creation: Generating audio content in multiple languages.
  • Assistive Technology: Providing speech output for individuals with disabilities.
  • Language Learning: Generating audio for language learning materials.
  • Game Development: Creating character voices.
  • Audiobook Creation: Converting text to speech for audiobooks.
  • Virtual Assistants/Chatbots: Powering voice interactions in conversational AI.
  • Dubbing and Voice-Over: Automating voice-over tasks.
  • Research: A platform for further research in TTS and voice cloning.
fish-speech screenshot