This repository serves as a curated, daily updated directory of cutting-edge research and projects in audio AI, covering areas like speech recognition, music generation, and text-to-speech. It aims to provide researchers and practitioners with a centralized, easily navigable resource for staying abreast of the latest advancements in the field.

How It Works

The project aggregates links and information from a wide array of sources including arXiv, Hugging Face, Twitter, GitHub trending, Papers With Code, and WeChat. This multi-source approach ensures comprehensive coverage of new publications, code repositories, and discussions, providing a broad overview of the audio AI landscape.

Quick Start & Requirements

This is a curated list, not a runnable software project. No installation or specific requirements are needed to browse the content.

Highlighted Details

• Daily tracking of papers, projects, and resources.
• Covers a wide spectrum of audio AI subfields: ASR, Encodec, Audio Generation, Music Generation, TTS, Voice Omni, Zero-Shot TTS.
• Aggregates content from diverse sources like arXiv, Hugging Face, GitHub, and Twitter.
• Includes surveys, projects, datasets, toolkits, and products for each subfield.

Maintenance & Community

The project is actively maintained, with daily updates ensuring the information remains current. Community engagement channels are not explicitly mentioned in the README.

Licensing & Compatibility

The repository itself is a list of links and does not contain code that would typically be subject to software licensing. The licensing of the linked external resources would vary.

Limitations & Caveats

As a curated list, the depth of information for each entry is limited to what is available from the source. The project does not host or provide direct access to the papers or code themselves.