11th Annual Conference of the International Speech Communication Association

Makuhari, Chiba, Japan
September 26-30. 2010

Floor Holder Detection and End of Speaker Turn Prediction in Meetings

Alfred Dielmann, Giulia Garau, Hervé Bourlard

Idiap Research Institute, Switzerland

We propose a novel fully automatic framework to detect which meeting participant is currently holding the conversational floor and when the current speaker turn is going to finish. Two sets of experiments were conducted on a large collection of multiparty conversations: the AMI meeting corpus. Unsupervised speaker turn detection was performed by post-processing the speaker diarization and the speech activity detection outputs. A supervised end-of-speaker-turn prediction framework, based on Dynamic Bayesian Networks and automatically extracted multimodal features (related to prosody, overlapping speech, and visual motion), was also investigated. These novel approaches resulted in good floor holder detection rates (13.2% Floor Error Rate), attaining state of the art end-of-speaker-turn prediction performances.

Full Paper

Bibliographic reference.  Dielmann, Alfred / Garau, Giulia / Bourlard, Hervé (2010): "Floor holder detection and end of speaker turn prediction in meetings", In INTERSPEECH-2010, 2306-2309.