Summary of Talk with Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction, by Haoqiu Yan et al.
Talk With Human-like Agents: Empathetic Dialogue Through Perceptible Acoustic Reception and Reaction
by Haoqiu Yan, Yongxin Zhu, Kai Zheng, Bing Liu, Haoyu Cao, Deqiang Jiang, Linli Xu
First submitted to arxiv on: 18 Jun 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 paper proposes PerceptiveAgent, an empathetic multi-modal dialogue system that integrates speech modality perception to discern deeper meanings beyond literal interpretations. By employing Large Language Models (LLMs) as a cognitive core, the agent perceives acoustic information from input speech and generates responses based on speaking styles described in natural language. Experimental results show that PerceptiveAgent excels in contextual understanding by accurately discerning speakers’ true intentions, producing nuanced and expressive spoken dialogues. |
| Low | GrooveSquid.com (original content) | Low Difficulty Summary This paper introduces an empathetic dialogue system called PerceptiveAgent. It uses large language models to understand what people mean when they speak. The agent looks at the sound of someone’s voice too, not just what they say. This helps it give more thoughtful responses that take into account how people feel, even if their words don’t exactly match their emotions. |
Keywords
» Artificial intelligence » Multi modal
