NDLI: Multi-Stream Asynchrony Dynamic Bayesian Network Model for Audio-Visual Continuous Speech Recognition

Content Provider	IEEE Xplore Digital Library
Author	Guoyun Lv Dongmei Jiang Rongchun Zhao Xiaoyue Jiang Sahli, H.
Copyright Year	2007
Description	Author affiliation: Northwestern Polytech. Univ., Xi'an (Guoyun Lv; Dongmei Jiang; Rongchun Zhao; Xiaoyue Jiang)
Abstract	How best to describe the asynchrony of the speech and lip motion is a key problem of audio-visual speech recognition model. A multi-stream asynchrony dynamic Bayesian network (MS-ADBN) model is brought forward for audio-visual speech recognition, and in this model, audio stream and visual stream are synchronous in word node, while between the word nodes, each stream has its own independent phone, phone transition and observation vector node, and word transition probability is determined by audio stream and visual stream together. For each stream, each word is composed of its corresponding phones, and each phone is associated with observation feature (audio feature for audio stream and visual feature for visual stream), with some probability modeled by Gaussian mixed model. Compare with general multi-stream HMM, MS-ADBN model describes the asynchrony of audio stream and visual stream to the word level. The experiment results on continuous digit audio visual database show that: compare with multi-stream HMM, in the mismatch noise environment, an average improvement of 10.07% are obtained for MS-ADBN model.
Starting Page	418
Ending Page	421
File Size	186128
Page Count	4
File Format	PDF
ISBN	9789612480363
DOI	10.1109/IWSSIP.2007.4381130
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2007-06-27
Publisher Place	Slovenia
Access Restriction	Subscribed
Rights Holder	Univ of Maribor
Subject Keyword	Shape Dynamic Bayesian Networks Spatial databases Electronic mail Computer science speech recognition Bayesian methods Bayesian Tangent Shape Model Hidden Markov models Speech recognition Streaming media Speech enhancement Signal processing audio-visual
Content Type	Text
Resource Type	Article

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