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Multimodal Interaction in Face-to-Face Dialogue

MINT 2026: Workshop on Multimodal Interaction in Face-to-Face Dialogue

In conjunction with
Empirical Methods in Natural Language Processing 2026
October 24-29, 2026
HungExpo
Budapest, Hungary

NLP Machine Learning

Covers multimodal modeling of face-to-face conversation, including speech, gesture, and gaze. Face-to-face conversation carries meaning in gesture, gaze and timing that a transcript loses entirely. The difficulty is data, since multimodal dialogue corpora are expensive to collect and annotate and rarely transfer across cultures. Annotation is also inherently interpretive, since two annotators may reasonably disagree about what a gesture conveyed.

  For more information, visit the workshop website

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