tailieunhanh - Báo cáo khoa học: "An Efficient Statistical Speech Act Type Tagging System for Speech Translation Systems"

This paper describes a new efficient speech act type tagging system. This system covers the tasks of (1) segmenting a turn into the optimal number of speech act units (SA units), and (2) assigning a speech act type tag (SA tag) to each SA unit. Our method is based on a theoretically clear statistical model that integrates linguistic, acoustic and situational information. We report tagging experiments on Japanese and English dialogue corpora manually labeled with SA tags. | An Efficient Statistical Speech Act Type Tagging System for Speech Translation Systems Hideki Tanaka and Akio Yokoo ATR Interpreting Telecommunications Research Laboratories 2-2 Hikaridai Seika-cho Soraku-gun Kyoto 619-0288 Japan tanakahIayokoo @ Abstract This paper describes a new efficient speech act type tagging system. This system covers the tasks of 1 segmenting a turn into the optimal number of speech act units SA units and 2 assigning a speech act type tag SA tag to each SA unit. Our method is based on a theoretically clear statistical model that integrates linguistic acoustic and situational information. We report tagging experiments on Japanese and English dialogue corpora manually labeled with SA tags. We then discuss the performance difference between the two languages. We also report on some translation experiments on positive response expressions using SA tags. 1 Introduction This paper describes a statistical speech act type tagging system that utilizes linguistic acoustic and situational features. This work can be viewed as a study on automatic Discourse Tagging whose objective is to assign tags to discourse units in texts or dialogues. Discourse tagging is studied mainly from two different viewpoints . linguistic and engineering viewpoints. The work described here belongs to the latter group. More specifically we are interested in automatically recognizing the speech act types of utterances and in applying them to speech translation systems. Several studies on discourse tagging to date have been motivated by engineering applications. The early studies by Nagata and Morimoto 1994 and Reithinger and Maier 1995 showed the possibility of predicting dialogue act tags for next utterances with statistical methods. These studies however presupposed properly segmented utterances which is not a realistic assumption. In contrast to this assumption automatic utterance segmentation or discourse segmentation is desired here. Discourse segmentation

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