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PRISM addresses a critical bottleneck in conversational AI by decoupling speech processing into coordinated agents that preserve acoustic cues lost in standard pipelines. By introducing a prosody-to-language translation mechanism, the framework stabilizes large language model reasoning to ensure both semantic accuracy and emotional alignment in spoken dialogue. This research advances the state of empathetic voice assistants through interpretable control over emotion integration rather than relying on opaque end-to-end models.
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PRISM: Prosody-Integrated Multi-Agent Reasoning Framework for Empathetic Spoken Dialogue

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arXiv:2606.12902v1 Announce Type: new Abstract: 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.

Abstract: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: this https URL.

Computation and Language (cs.CL)

arXiv:2606.12902 [cs.CL]

(or arXiv:2606.12902v1 [cs.CL] for this version)

https://doi.org/10.48550/arXiv.2606.12902 Focus to learn more arXiv-issued DOI via DataCite (pending registration)

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