PRISM：用于共情口语对话的韵律集成多智能体推理框架
PRISM: Prosody-Integrated Multi-Agent Reasoning Framework for Empathetic Spoken Dialogue
AI总结：
提出PRISM多智能体框架，通过解耦语音感知、响应生成和语音合成，并引入韵律到语言翻译机制，实现共情口语对话中的韵律适当性和知识集成。
摘要：
共情口语对话系统不仅需要语义上合适的回应，还需要情感上一致的韵律表达。然而，级联流水线通常在语音到文本转换过程中丢弃声学线索，而端到端语音模型缺乏对情感和知识集成的可解释控制。为了解决这些挑战，我们提出了PRISM，一个用于共情口语对话的多智能体框架，它将语音感知、响应生成和语音合成解耦为协调的组件。PRISM引入了一种韵律到语言的翻译机制来稳定大语言模型的推理，并支持按需调用外部知识工具以生成共情对话。实验结果表明，PRISM在客观和主观指标上均实现了共情性、韵律适当性和文本响应生成质量的一致改进。我们的代码可在以下网址获取：this https URL。
英文摘要：
Empathetic spoken dialogue systems require not only semantically appropriate responses but also emotionally aligned prosodic expression. However, cascade pipelines often discard acoustic cues during speech-to-text conversion, while end-to-end speech models lack interpretable control over emotion and knowledge integration. To address these challenges, we propose PRISM, a multi-agent framework for empathetic spoken dialogue that decouples speech perception, response generation, and speech synthesis into coordinated components. PRISM introduces a prosody-to-language translation mechanism to stabilize large language model reasoning and enables on-demand invocation of external knowledge tools for empathetic dialogue generation. Experimental results demonstrate that PRISM achieves consistent improvements in empathy, prosodic appropriateness, and text response generation quality across objective and subjective metrics. Our code is available at: https://github.com/Bxzfrm/PRISM.
机构、总结、中文摘要均由AI分析而来，可能存在错误，请以论文正文为准。
