Presentation 2004/12/13
Asynchronous Articulatory Feature Recognition Using Dynamic Bayesian Networks
Mirjam WESTERN, Joe FRANKEL, Simon KING,
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Abstract(in English) This paper builds on previous work where dynamic Bayesian networks (DBN) were proposed as a model for articulatory feature recognition. Using DBNs makes it possible to model the dependencies between features, an addition to previous approaches which was found to improve feature recognition performance. The DBN results were promising, giving close to the accuracy of artificial neural nets (ANNs). However, the system was trained on canonical labels, leading to an overly strong set of constraints on feature co-occurrence. In this study, we describe an embedded training scheme which learns a set of data-driven asynchronous feature changes where supported in the data. Using a subset of the OGI Numbers corpus, we describe articulatory feature recognition experiments using both canonically-trained and asynchronous-feature DBNs. Performance using DBNs is found to exceed that of ANNs trained on an identical task, giving a higher recognition accuracy. Furthermore, inter-feature dependencies result in a more structured model, giving rise to fewer feature combinations in the recognition output. In addition to an empirical evaluation of this modeling approach, we give a qualitative analysis, investigating the asynchrony found through our data-driven method and interpreting it using linguistic knowledge.
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Keyword(in English) Articulatory feature recognition / dynamic Bayesian networks
Paper # NLC2004-47,SP2004-87
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Committee NLC
Conference Date 2004/12/13(1days)
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Registration To Natural Language Understanding and Models of Communication (NLC)
Language ENG
Title (in Japanese) (See Japanese page)
Sub Title (in Japanese) (See Japanese page)
Title (in English) Asynchronous Articulatory Feature Recognition Using Dynamic Bayesian Networks
Sub Title (in English)
Keyword(1) Articulatory feature recognition
Keyword(2) dynamic Bayesian networks
1st Author's Name Mirjam WESTERN
1st Author's Affiliation Centre for Speech Technology Research, University of Edinburgh()
2nd Author's Name Joe FRANKEL
2nd Author's Affiliation Centre for Speech Technology Research, University of Edinburgh
3rd Author's Name Simon KING
3rd Author's Affiliation Centre for Speech Technology Research, University of Edinburgh
Date 2004/12/13
Paper # NLC2004-47,SP2004-87
Volume (vol) vol.104
Number (no) 538
Page pp.pp.-
#Pages 6
Date of Issue