Papers by M. Hamza Mughal

2 papers
Enhancing Spoken Discourse Modeling in Language Models Using Gestural Cues (2025.acl-long)

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Challenge: linguistic research shows that non-verbal cues, such as gestures, play a crucial role in spoken discourse.
Approach: They propose to integrate gestures into language models by embedding human motion sequences into discrete gesture tokens and aligning them with text embeddables.
Outcome: The proposed model improves on spoken discourse, the authors show . the study aims to improve the accuracy of discourse markers and quantifiers .
Modeling Turn-Taking with Semantically Informed Gestures (2026.findings-eacl)

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Challenge: Existing computational models of turn-taking relied on verbal cues and prosody.
Approach: They propose a framework that integrates text, audio, and gestures to model multimodal turn-taking using semantic annotations.
Outcome: The proposed framework shows that incorporating semantically guided gestures yields consistent performance gains over baselines.

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