Open Your Model's Eyes: Video and Context-Aware Multimodal Backchannel Prediction
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Computer Science > Computer Vision and Pattern Recognition
arXiv:2607.22729 (cs)
[Submitted on 22 Jul 2026]
Title:Open Your Model's Eyes: Video and Context-Aware Multimodal Backchannel Prediction
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Abstract:Backchannels, which signal listener states like empathy and understanding, are fundamental to natural human interaction. However, current approaches rely solely on audio and text. This omits crucial visual cues, such as facial expressions and gestures, as well as broader conversational contexts, which are necessary for accurate prediction. In this paper, we introduce Context-Aware Multimodal Alignment for Backchannel Prediction (CAMA-BC), a novel framework that leverages visual information through Multi-Layer Multimodal Alignment (MMA). Our alignment process comprises two stages. First, Context Alignment (MMA-CA) utilizes unlabeled dialogues with videos to capture conversational contexts. Next, Backchannel Alignment (MMA-BA) fine-tunes the representations specifically for backchannel prediction. Experimental results show that CAMA-BC significantly outperforms both existing methods and simple multimodal baselines, with particular effectiveness in recognizing complex backchannels such as empathy.
| Comments: | 18 pages, Accepted at ACL 2026 |
| Subjects: | Computer Vision and Pattern Recognition (cs.CV); Computation and Language (cs.CL) |
| Cite as: | arXiv:2607.22729 [cs.CV] |
| (or arXiv:2607.22729v1 [cs.CV] for this version) | |
| https://doi.org/10.48550/arXiv.2607.22729
arXiv-issued DOI via DataCite (pending registration)
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| Journal reference: | Proceedings of the 64th Annual Meeting of the Association for Computational Linguistics (Volume 1: Long Papers), Association for Computational Linguistics, pp. 3738-3755, 2026 |
| Related DOI: | https://doi.org/10.18653/v1/2026.acl-long.171
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View a PDF of the paper titled Open Your Model's Eyes: Video and Context-Aware Multimodal Backchannel Prediction, by Min-Jae Kim and 3 other authors
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