Speech act modeling and verification in spoken dialogue systems

Chung Hsien Wu, Jui Feng Yen, Gwo Lang Yan

研究成果: Chapter

1 引文 斯高帕斯(Scopus)

摘要

Speech act, an essential element of conversation, underlies the principle that an utterance in a dialogue is an action being performed by a speaker. Since speech acts do convey speakers’ intentions and opinions, it is key for the computer to identify and verify the speech act of a user’s utterance in a spoken dialogue system. This chapter presents a few approaches to speech act identification and verification in Chinese spoken dialogue systems. Approaches using ontology-based partial pattern trees and semantic dependency graphs (SDGs) for speech act modeling are described. A verification mechanism using a latent semantic analysis (LSA) based Bayesian belief model (BBM) is adopted to improve the performance of speech act identification. Experimental results show the SDG-based approach outperforms the Bayes’ classifier and the ontology-based partial pattern trees. By integrating discourse analysis into the SDG-based approach, the results show improvements obtained not only in the speech act identification accuracy rate, but also in the performance of semantic object extraction. Furthermore, LSA-based BBM for speech act verification further improves the performance of speech act identification.

原文English
主出版物標題Advances in Chinese Spoken Language Processing
發行者World Scientific Publishing Co.
頁面321-340
頁數20
ISBN(電子)9789812772961
ISBN(列印)9812569049, 9789812569042
DOIs
出版狀態Published - 2006 1月 1

All Science Journal Classification (ASJC) codes

  • 一般電腦科學

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