Abstract
In this paper, we report on the infrastructure we have developed to support our research on multimodal cues for understanding meetings. With our focus on multimodality, we investigate the interaction among speech, gesture, posture, and gaze in meetings. For this purpose, a high quality multimodal corpus is being produced.
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Chen, L. et al. (2006). VACE Multimodal Meeting Corpus. In: Renals, S., Bengio, S. (eds) Machine Learning for Multimodal Interaction. MLMI 2005. Lecture Notes in Computer Science, vol 3869. Springer, Berlin, Heidelberg. https://doi.org/10.1007/11677482_4
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DOI: https://doi.org/10.1007/11677482_4
Publisher Name: Springer, Berlin, Heidelberg
Print ISBN: 978-3-540-32549-9
Online ISBN: 978-3-540-32550-5
eBook Packages: Computer ScienceComputer Science (R0)