Automatically predicting dialogue structure using prosodic features
Speech Communication - Dialogue and prosody
Dynamic bayesian networks: representation, inference and learning
Dynamic bayesian networks: representation, inference and learning
Dialogue act modeling for automatic tagging and recognition of conversational speech
Computational Linguistics
Factored language models and generalized parallel backoff
NAACL-Short '03 Proceedings of the 2003 Conference of the North American Chapter of the Association for Computational Linguistics on Human Language Technology: companion volume of the Proceedings of HLT-NAACL 2003--short papers - Volume 2
UAI'00 Proceedings of the Sixteenth conference on Uncertainty in artificial intelligence
The AMI meeting corpus: a pre-announcement
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Toward joint segmentation and classification of dialog acts in multiparty meetings
MLMI'05 Proceedings of the Second international conference on Machine Learning for Multimodal Interaction
Communicative gestures in coreference identification in multiparty meetings
Proceedings of the 2009 international conference on Multimodal interfaces
Robust real time face tracking for the analysis of human behaviour
MLMI'07 Proceedings of the 4th international conference on Machine learning for multimodal interaction
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We propose a joint segmentation and classification approach for the dialogue act recognition task on natural multi-party meetings (ICSI Meeting Corpus). Five broad DA categories are automatically recognised using a generative Dynamic Bayesian Network based infrastructure. Prosodic features and a switching graphical model are used to estimate DA boundaries, in conjunction with a factored language model which is used to relate words and DA categories. This easily generalizable and extensible system promotes a rational approach to the joint DA segmentation and recognition task, and is capable of good recognition performance.