Papers by Gyuhyeon Seo

1 papers
SpeakerSleuth: Can Large Audio-Language Models Judge Speaker Consistency across Multi-turn Dialogues? (2026.acl-long)

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Challenge: Large Audio-Language Models (LALMs) are a popular approach for evaluating speech quality, yet their ability to assess speaker consistency across multi-turn dialogues remains unexplored.
Approach: They construct 1,818 human-verified evaluation instances across four datasets spanning synthetic and real speech, with controlled acoustic difficulty.
Outcome: The proposed model performs better in comparing and ranking acoustic variants, demonstrating inherent acustic discrimination capabilities.

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