ER-EDF: A Psychology-Grounded Emotion Regulation Framework for Speech Empathetic Dialogue Generation in Large Audio-Language Models

arXiv:2609.15089v2 Announce Type: replace Abstract: In human conversation, empathy involves not only recognizing a partner's emotion but also regulating it, listeners identify the emotional state, select a suitable regulation strategy, and implement it in their reply. Current large audio-language models (LALMs) largely map perceived emotion directly onto a response, skipping this regulation process. As a result, their responses tend to mirror the user's affect or offer generic sympathy. We propose ER-EDF, a psychology-grounded framework for empathetic dialogue that follows the three stages of

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