Gwo-Lang Yan

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Most automatic speech recognizers (ASRs) concentrate on read speech, which is different from spontaneous speech with disfluencies. ASRs cannot deal with speech with a high rate of disfluencies such as filled pauses, repetitions, lengthening, repairs, false starts and silence pauses. In this paper, we focus on the feature analysis and modeling of the filled(More)
In a spoken dialog system, it is an important problem for the computer to identify the speech act (SA) from a user’s utterance due to the variability of spoken language. In this paper, a corpus-based fuzzy fragment-class Markov model (FFCMM) is proposed to model the syntactic characteristics of a speech act and used to choose the speech act candidates. A(More)
In a spoken dialogue system, the intention is the most important component for speech understanding. In this paper, we propose a corpus-based hidden Markov model (HMM) to model the intention of a sentence. Each intention is represented by a sequence of word segment categories determined by a task-specific lexicon and a corpus. In the training procedure,(More)
In this paper, the prosodic information, a very special and important feature in Mandarin speech, is used for Mandarin telephone speech utterance verification. A two-stage strategy, with recognition followed by verification, is adopted. For keyword recognition, 59 context-independent subsyllables, i.e., 22 INITIAL’s and 37 FINAL’s in Mandarin speech, and(More)
OBJECTIVES A novel analysis was undertaken to select a significant ultrasonographic parameter (USP) for classifying fetuses to support artificial neural network (ANN), and thus to enhance the accuracy of fetal weight estimation. METHODS In total, 2127 singletons were examined by prenatal ultrasound within 3 days before delivery. First, correlation(More)
This paper describes an approach for flexible speech act identification of spontaneous speech with disfluency. In this approach, semantic information, syntactic structure, and fragment features of an input utterance are statistically encapsulated into a proposed sp eech act hidden Markov model (SAHMM) to characterize the speech act. To deal with the(More)
Correct registration in the hospital can avoid wasting medical resources and shorten the time of diagnoses. The purpose of this research is to build a hospital registration system to help patients register in the hospital. This system can assist patients, who are not familiar with medical topics, to determine which department they should register by the(More)