Sentence compression using statistical information about dependency path length

Authors:
Kiwamu Yamagata;Satoshi Fukutomi;Kazuyuki Takagi;Kazuhiko Ozeki
Affiliations:
The University of Electro-Communications, Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan;The University of Electro-Communications, Tokyo, Japan
Venue:
TSD'06 Proceedings of the 9th international conference on Text, Speech and Dialogue
Year:
2006

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Abstract

This paper is concerned with the use of statistical information about dependency path length for sentence compression The sentence compression method employed here requires a quantity called inter-phrase dependency strength In the training process, original sentences are parsed, and the number of tokens is counted for each pair of phrases, connected with each other by a dependency path of certain length, that survive as a modifier-modified phrase pair in the corresponding compressed sentence in the training corpus The statistics is exploited to estimate the inter-phrase dependency strength required in the sentence compression process Results of subjective evaluation shows that the present method outperforms the conventional one of the same framework where the distribution of dependency distance is used to estimate the inter-phrase dependency strength.