EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Spoken Dialogue Systems

• URL: http://arxiv.org/abs/2508.17623v2
• Date: Tue, 26 Aug 2025 02:30:26 GMT
• Title: EMO-Reasoning: Benchmarking Emotional Reasoning Capabilities in Spoken Dialogue Systems
• Authors: Jingwen Liu, Kan Jen Cheng, Jiachen Lian, Akshay Anand, Rishi Jain, Faith Qiao, Robin Netzorg, Huang-Cheng Chou, Tingle Li, Guan-Ting Lin, Gopala Anumanchipalli,
• Abstract summary: EMO-Reasoning is a benchmark for assessing emotional coherence in dialogue systems.<n>We propose the Cross-turn Emotion Reasoning Score to assess the emotion transitions in multi-turn dialogues.
• Score: 25.920610612373608
• License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
• Abstract: Speech emotions play a crucial role in human-computer interaction, shaping engagement and context-aware communication. Despite recent advances in spoken dialogue systems, a holistic system for evaluating emotional reasoning is still lacking. To address this, we introduce EMO-Reasoning, a benchmark for assessing emotional coherence in dialogue systems. It leverages a curated dataset generated via text-to-speech to simulate diverse emotional states, overcoming the scarcity of emotional speech data. We further propose the Cross-turn Emotion Reasoning Score to assess the emotion transitions in multi-turn dialogues. Evaluating seven dialogue systems through continuous, categorical, and perceptual metrics, we show that our framework effectively detects emotional inconsistencies, providing insights for improving current dialogue systems. By releasing a systematic evaluation benchmark, we aim to advance emotion-aware spoken dialogue modeling toward more natural and adaptive interactions.

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