Visual speaker localization aided by acoustic models
MM '09 Proceedings of the 17th ACM international conference on Multimedia
Dialocalization: Acoustic speaker diarization and visual localization as joint optimization problem
ACM Transactions on Multimedia Computing, Communications, and Applications (TOMCCAP)
A review on speaker diarization systems and approaches
Speech Communication
Audiovisual diarization of people in video content
Multimedia Tools and Applications
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Segmenting different individuals in a group meeting and their speech is an important first step for various tasks such as meeting transcription, automatic camera panning, multimedia retrieval and monologue detection. In this effort, given a meeting room video, we attempt to segment individual person's speech and localize them in the video, based on data from a single audio and video source. The segmentation method is driven by audio and enhanced by video cues. We used Bayesian Information Criterion (BIC) to segment the feature vector streams and graph spectral partitioning to cluster them. We compare our results with audio based segmentation method and our localization technique with the commonly used mutual information.