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A Statistical Prediction Model of Speakers' Intentions in a Goal-Oriented Dialogue  

Kim, Dong-Hyun (㈜다이퀘스트연구소)
Kim, Hark-Soo (강원대학교 컴퓨터정보통신공학)
Seo, Jung-Yun (서강대학교 컴퓨터공학과)
Publication Information
Journal of KIISE:Software and Applications / v.35, no.9, 2008 , pp. 554-561 More about this Journal
Abstract
Prediction technique of user's intention can be used as a post-processing method for reducing the search space of an automatic speech recognizer. Prediction technique of system's intention can be used as a pre-processing method for generating a flexible sentence. To satisfy these practical needs, we propose a statistical model to predict speakers' intentions that are generalized into pairs of a speech act and a concept sequence. Contrary to the previous model using simple n-gram statistic of speech acts, the proposed model represents a dialogue history of a current utterance to a feature set with various linguistic levels (i.e. n-grams of speech act and a concept sequence pairs, clue words, and state information of a domain frame). Then, the proposed model predicts the intention of the next utterance by using the feature set as inputs of CRFs (Conditional Random Fields). In the experiment in a schedule management domain, The proposed model showed the precision of 76.25% on prediction of user's speech act and the precision of 64.21% on prediction of user's concept sequence. The proposed model also showed the precision of 88.11% on prediction of system's speech act and the Precision of 87.19% on prediction of system's concept sequence. In addition, the proposed model showed 29.32% higher average precision than the previous model.
Keywords
Intention prediction; speech act prediction; concept sequence prediction;
Citations & Related Records
Times Cited By KSCI : 1  (Citation Analysis)
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