This repository provides SpeechGPT, a series of multimodal large language models designed to process and generate speech alongside text. It aims to empower LLMs with intrinsic cross-modal conversational abilities, enabling them to understand and respond to spoken language and instructions. The project targets researchers and developers working on advanced conversational AI and multimodal understanding.

How It Works

SpeechGPT integrates speech processing capabilities directly into large language models, allowing for end-to-end multimodal input and output. This approach bypasses the need for separate speech-to-text and text-to-speech modules, potentially leading to more natural and contextually aware interactions. The project also introduces SpeechTokenizer, a unified speech tokenizer for speech language models, and SpeechGPT-Gen for scaling chain-of-information speech generation.

Highlighted Details

• SpeechGPT is presented as the first multimodal LLM capable of perceiving and generating multimodal content following multimodal human instructions.
• Introduces SpeechTokenizer, a unified speech tokenizer for speech language models.
• Features SpeechGPT-Gen for scaling chain-of-information speech generation.
• Related work includes AnyGPT for unified multimodal LLM with discrete sequence modeling and SpeechAgents for human-communication simulation.

Maintenance & Community

The project is associated with authors from institutions like Fudan University. Recent updates include the release of SpeechGPT-Gen and AnyGPT. Links to papers, demos, and GitHub repositories for related projects are provided.

Licensing & Compatibility

The README does not explicitly state the license type or any restrictions.

Limitations & Caveats

The README focuses on the capabilities and releases without detailing specific limitations, hardware requirements, or setup instructions. The project appears to be research-oriented, and production-readiness is not specified.