Class-based n-gram models of natural language
Computational Linguistics
Speech repairs, intonational boundaries and discourse markers: modeling speakers' utterances in spoken dialog
C++
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Computational Linguistics
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ACL '83 Proceedings of the 21st annual meeting on Association for Computational Linguistics
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Natural Language Engineering
Robust, finite-state parsing for spoken language understanding
ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on Computational Linguistics
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ACL '99 Proceedings of the 37th annual meeting of the Association for Computational Linguistics on 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
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NAACL '01 Proceedings of the second meeting of the North American Chapter of the Association for Computational Linguistics on Language technologies
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International Journal of Human-Computer Studies
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To understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse markers. In this paper, we argue that these problems must be resolved together, and that they must be resolved early in the processing stream. We put forward a statistical language model that resolves these problem, does POS tagging, and can be used as the language model of a speech recognizer. We find that by accounting for the interactions between these tasks that the performance on each task improves, as does POS tagging and perplexity.