Procedure for quantitatively comparing the syntactic coverage of English grammars
HLT '91 Proceedings of the workshop on Speech and Natural Language
Building a large annotated corpus of English: the penn treebank
Computational Linguistics - Special issue on using large corpora: II
A maximum-entropy-inspired parser
NAACL 2000 Proceedings of the 1st North American chapter of the Association for Computational Linguistics conference
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
Markov parsing: lattice rescoring with a statistical parser
ACL '02 Proceedings of the 40th Annual Meeting on Association for 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
Parsing and disfluency placement
EMNLP '02 Proceedings of the ACL-02 conference on Empirical methods in natural language processing - Volume 10
A TAG-based noisy channel model of speech repairs
ACL '04 Proceedings of the 42nd Annual Meeting on Association for Computational Linguistics
Effective use of prosody in parsing conversational speech
HLT '05 Proceedings of the conference on Human Language Technology and Empirical Methods in Natural Language Processing
Where Do Parsing Errors Come From
TSD '08 Proceedings of the 11th international conference on Text, Speech and Dialogue
Wide-coverage parsing of speech transcripts
IWPT '09 Proceedings of the 11th International Conference on Parsing Technologies
Automatic identification of discourse markers in dialogues: An in-depth study of like and well
Computer Speech and Language
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This paper evaluates the benefit of deleting fillers (e.g. you know, like) early in parsing conversational speech. Readability studies have shown that disfluencies (fillers and speech repairs) may be deleted from transcripts without compromising meaning (Jones et al., 2003), and deleting repairs prior to parsing has been shown to improve its accuracy (Charniak and Johnson, 2001). We explore whether this strategy of early deletion is also beneficial with regard to fillers. Reported experiments measure the effect of early deletion under in-domain and out-of-domain parser training conditions using a state-of-the-art parser (Charniak, 2000). While early deletion is found to yield only modest benefit for in-domain parsing, significant improvement is achieved for out-of-domain adaptation. This suggests a potentially broader role for disfluency modeling in adapting text-based tools for processing conversational speech.