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標題Title: Speech Act Modeling and Verification of Spontaneous Speech With Disfluency in a Spoken Dialogue System
作者Authors: 顏國郎,Chung-Hsien Wu..等
上傳單位Department: 資訊工程系
上傳時間Date: 2009-12-1
上傳者Author: 顏國郎
審核單位Department: 資訊工程系
審核老師Teacher: 顏國郎
檔案類型Categories: 論文Thesis
關鍵詞Keyword: Bayesian belief model, disfluency modeling,, speech act modeling, spoken dialogue.
摘要Abstract: Abstract—This work presents an approach to modeling speech
acts and verifying spontaneous speech with disfluency in a spoken
dialogue system. According to this approach, semantic information,
syntactic structure and fragment class of an input utterance
are statistically encapsulated in a proposed speech act hidden
Markov model (SAHMM) to characterize the speech act. An interpolation
mechanism is exploited to re-estimate the state transition
probability in SAHMM, to deal with the problem of disfluency in
a sparse training corpus. Finally, a Bayesian belief model (BBM),
based on latent semantic analysis (LSA), is adopted to verify the
potential speech acts and output the final speech act. Experiments
were conducted to evaluate the proposed approach using a spoken
dialogue system for providing air travel information. A testing
database from 25 speakers, with 480 dialogues that include 3038
sentences, was established and used for evaluation. Experimental
results show that the proposed approach identifies 95.3% of
speech act at a rejection rate of 5%, and the semantic accuracy
is 4.2% better than that obtained using a keyword-based system.
The proposed strategy also effectively alleviates the disfluency
problem in spontaneous speech.

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