Punctuating speech for information extraction

This paper studies the effect of automatic sentence boundary detection and comma prediction on entity and relation extraction in speech. We show that punctuating the machine generated transcript according to maximum F-measure of period and comma annotation results in suboptimal information extraction. Precisely, period and comma decision thresholds can be chosen in order to improve the entity value score and the relation value score by 4% relative. Error analysis shows that preventing noun-phrase splitting by generating longer sentences and fewer commas can be harmful for IE performance. Indeed, it seems that missed punctuation allows syntactic parsers to merge noun-phrases and prevent the extraction of correct information.

• Type: Conference
• Year: 2008
• Where: ICASSP
• Authors: Benoît Favre, Ralph Grishman, Dustin Hillard, Heng Ji, Dilek Hakkani-Tür, Mari Ostendorf
• Keywords: Comma Decision Thresholds, Comma Prediction, Commas, ICASSP 2008, Signal Processing