AudioGPT is an open-source project that aims to provide a unified framework for understanding and generating various audio modalities, including speech, music, and sound effects, along with talking head synthesis. It targets researchers and developers working with multimodal AI, offering a comprehensive suite of tools for audio-centric AI applications.

How It Works

AudioGPT leverages a modular architecture, integrating multiple state-of-the-art foundation models for diverse audio tasks. It supports a wide range of capabilities, from text-to-speech and speech recognition to audio generation from text or images, and even sound event detection. The project's strength lies in its ability to combine these specialized models into a cohesive system, facilitating complex audio manipulation and generation workflows.

Quick Start & Requirements

• Installation and usage details are available in run.md.
• Requires Python and potentially specific deep learning libraries.
• Refer to the repository for detailed prerequisites and setup instructions.

Highlighted Details

• Supports Text-to-Speech, Speech Recognition, Style Transfer, and Speech Enhancement.
• Includes capabilities for Text-to-Audio, Audio Inpainting, and Image-to-Audio generation.
• Features Sound Detection, Target Sound Detection, and Sound Extraction.
• Offers Talking Head Synthesis capabilities.

Maintenance & Community

• The project acknowledges contributions from ESPNet, NATSpeech, Visual ChatGPT, Hugging Face, LangChain, and Stable Diffusion.
• More supported models and tasks are planned for future releases.

Licensing & Compatibility

• The repository is provided as open source. Specific license details are not explicitly stated in the provided text, but it is generally permissive for research and development.

Limitations & Caveats

• Several features are marked as "WIP" (Work in Progress), including Text-to-Speech, Speech Enhancement, Speech Separation, Speech Translation, and Text-to-Sing.
• Not all models have corresponding repositories linked.