Summary of Omniflatten: An End-to-end Gpt Model For Seamless Voice Conversation, by Qinglin Zhang et al.
OmniFlatten: An End-to-end GPT Model for Seamless Voice Conversation
by Qinglin Zhang, Luyao Cheng, Chong Deng, Qian Chen, Wen Wang, Siqi Zheng, Jiaqing Liu, Hai Yu, Chaohong Tan, Zhihao Du, Shiliang Zhang
First submitted to arxiv on: 23 Oct 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Sound (cs.SD); Audio and Speech Processing (eess.AS)
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| Summary difficulty | Written by | Summary |
|---|---|---|
| High | Paper authors | High Difficulty Summary Read the original abstract here |
| Medium | GrooveSquid.com (original content) | Medium Difficulty Summary The proposed OmniFlatten model is a novel End-to-End GPT-based system designed for full-duplex conversation, which enables simultaneous bidirectional communication. The model leverages a multi-stage post-training scheme to adapt a text large language model (LLM) backbone into a speech-text dialogue LLM, capable of generating text and speech in real-time. The training process involves modality alignment, half-duplex dialogue learning, and full-duplex dialogue learning, with standardized data using a flattening operation. This approach offers a simple modeling technique and a promising research direction for developing efficient and natural end-to-end full-duplex spoken dialogue systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The OmniFlatten model is a new way to make conversations between humans and computers feel more natural. It lets both parties talk at the same time, like we do when talking to each other. But making this work requires some clever tricks to handle things like interruptions, side comments, and overlapping speech. The researchers developed a special training process that helps their model understand how to generate text and speech quickly and naturally. They used data from multiple sources and applied a few secret sauce techniques to make it all work together smoothly. |
Keywords
» Artificial intelligence » Alignment » Gpt » Large language model
