Summary of Language Model Can Listen While Speaking, by Ziyang Ma et al.
Language Model Can Listen While Speaking
by Ziyang Ma, Yakun Song, Chenpeng Du, Jian Cong, Zhuo Chen, Yuping Wang, Yuxuan Wang, Xie Chen
First submitted to arxiv on: 5 Aug 2024
Categories
- Main: Computation and Language (cs.CL)
- Secondary: Artificial Intelligence (cs.AI); Human-Computer Interaction (cs.HC); Sound (cs.SD); Audio and Speech Processing (eess.AS)
GrooveSquid.com Paper Summaries
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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 paper explores the development of a novel language model that can engage in real-time spoken conversations with humans, allowing for interruptions and more natural interactions. The authors propose an end-to-end system called Listening-While-Speaking Language Model (LSLM) that combines a token-based decoder-only TTS for speech generation and a streaming self-supervised learning (SSL) encoder for real-time audio input. The LSLM is trained using three fusion strategies, with middle fusion achieving the best balance between speech generation and real-time interaction. The authors demonstrate the robustness of the model in two experimental settings, command-based FDM and voice-based FDM, and show its potential to enhance interactive speech dialogue systems. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary The paper creates a new language model that can have conversations with people in real time. This means the conversation can be interrupted or paused, like it would be in everyday life. The authors designed a special system called LSLM (Listening-While-Speaking Language Model) that can do this. It uses two parts: one to generate speech and another to listen to audio input. They tested different ways of combining these parts and found the best approach was to balance generation and interaction in real time. This model could be used to make conversation systems more natural and helpful. |
Keywords
» Artificial intelligence » Decoder » Encoder » Language model » Self supervised » Token
