Attention, intentions, and the structure of discourse
Computational Linguistics
C4.5: programs for machine learning
C4.5: programs for machine learning
Statistical methods for speech recognition
Statistical methods for speech recognition
Combining multiple knowledge sources for discourse segmentation
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
Utilizing statistical dialogue act processing in VERBMOBIL
ACL '95 Proceedings of the 33rd annual meeting on Association for Computational Linguistics
A prosodic analysis of discourse segments in direction-giving monologues
ACL '96 Proceedings of the 34th annual meeting on Association for Computational Linguistics
A stochastic Japanese morphological analyzer using a forward-DP backward-A* N-best search algorithm
COLING '94 Proceedings of the 15th conference on Computational linguistics - Volume 1
Summarizing multilingual spoken negotiation dialogues
ACL '00 Proceedings of the 38th Annual Meeting on Association for Computational Linguistics
Retrieving meaning-equivalent sentences for example-based rough translation
HLT-NAACL-PARALLEL '03 Proceedings of the HLT-NAACL 2003 Workshop on Building and using parallel texts: data driven machine translation and beyond - Volume 3
Dialogue act tagging for instant messaging chat sessions
ACLstudent '05 Proceedings of the ACL Student Research Workshop
Improving Korean speech acts analysis by using shrinkage and discourse stack
IJCNLP'05 Proceedings of the Second international joint conference on Natural Language Processing
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This paper describes a new efficient speech act type tagging system. This system covers the tasks of (1) segmenting a turn into the optimal number of speech act units (SA units), and (2) assigning a speech act type tag (SA tag) to each SA unit. Our method is based on a theoretically clear statistical model that integrates linguistic, acoustic and situational information. We report tagging experiments on Japanese and English dialogue corpora manually labeled with SA tags. We then discuss the performance difference between the two languages. We also report on some translation experiments on positive response expressions using SA tags.