Speech Communication - Special issue on interactive voice technology for telecommunication applications (IVITA '96)
Speech repairs, intonational boundaries and discourse markers: modeling speakers' utterances in spoken dialog
Improved Boosting Algorithms Using Confidence-rated Predictions
Machine Learning - The Eleventh Annual Conference on computational Learning Theory
A Brief Introduction to Boosting
IJCAI '99 Proceedings of the Sixteenth International Joint Conference on Artificial Intelligence
Supertagging: an approach to almost parsing
Computational Linguistics
A stochastic parts program and noun phrase parser for unrestricted text
ANLC '88 Proceedings of the second conference on Applied natural language processing
ACL '92 Proceedings of the 30th annual meeting on Association for Computational Linguistics
A syntactic framework for speech repairs and other disruptions
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
Edit detection and parsing for transcribed speech
NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
A relaxation method for understanding spontaneous speech utterances
HLT '91 Proceedings of the workshop on Speech and Natural Language
Statistical language modeling for speech disfluencies
ICASSP '96 Proceedings of the Acoustics, Speech, and Signal Processing, 1996. on Conference Proceedings., 1996 IEEE International Conference - Volume 01
| Hi-index | 0.00 |
Spontaneous human utterances in the context of human-human and human-machine dialogs are rampant with dysfluencies, and speech repairs. Furthermore, when recognized using a speech recognizer, these utterances produce a sequence of words with no identification of clausal units. Such long strings of words combined with speech errors pose a difficult problem for spoken language parsing and understanding. In this paper, we address the issue of editing speech repairs as well as segmenting user utterances into clause units with a view of parsing and understanding spoken language utterances. We present generative and discriminative models for this task and present evaluation results on the human-human conversations obtained from the Switch board corpus.