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Parsing Conversational Speech Using Enhanced Segmentation

By Jeremy G. Kahn, Mari Ostendorf and Ciprian Chelba


The lack of sentence boundaries and presence of dis-fluencies pose difficulties for parsing conversational speech. This work investigates the effects of au-tomatically detecting these phenomena on a proba-bilistic parser’s performance. We demonstrate that a state-of-the-art segmenter, relative to a pause-based segmenter, gives more than 45 % of the possible er-ror reduction in parser performance, and that presen-tation of interruption points to the parser improves performance over using sentence boundaries alone.

Year: 2004
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