Speech act modeling and verification in spoken dialogue systems

Chung Hsien Wu, Jui Feng Yen, Gwo Lang Yan

Research output: Chapter in Book/Report/Conference proceedingChapter


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.

Original languageEnglish
Title of host publicationAdvances in Chinese Spoken Language Processing
PublisherWorld Scientific Publishing Co.
Number of pages20
ISBN (Electronic)9789812772961
ISBN (Print)9812569049, 9789812569042
Publication statusPublished - 2006 Jan 1

All Science Journal Classification (ASJC) codes

  • Computer Science(all)


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