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This paper proposes an unsupervised method for analyzing speaker roles in multi-participant conversational speech. First, features for characterizing the differences of various roles are extracted from the outputs of speaker diarization. Then, an algorithm of role clustering based on the criterion of maximizing the inter-cluster distance without using any convergence threshold is proposed to obtain...
Processing spontaneous speech is one of the many challenges that automatic speech recognition systems have to deal with. The main characteristics of this kind of speech are disfluencies (filled pause, repetition, false start, etc.) and many studies have focused on their detection and correction. Spontaneous speech is defined in opposition to prepared speech, where utterances contain well-formed sentences...
Speaker role recognition in TV Broadcast News shows is addressed in this paper with a particular focus on speaker turn role labeling. A mixed approach combining speaker clustering and analysis of Automatic Speech Recognition output is proposed for assigning speaker turns a role among: anchor, reporter and other. 86% classification accuracy is obtained for automatically segmented speaker turns on a...
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