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- W2485890286 abstract "The basic building blocks of visual speech are the visemes. Unlike phonemes, the visemes are, however, confusable and easily distorted by the contexts in which they appear. Classifiers capable of distinguishing the minute difference among the different categories are desirable. In this chapter, we describe two Hidden Markov Model based techniques using the discriminative approach to increase the accuracy of visual speech recognition. The approaches investigated include Maximum Separable Distance (MSD) training strategy (Dong, 2005) and Two-channel training approach (Dong, 2005; Foo, 2003; Foo, 2002) The MSD training strategy and the Two-channel training approach adopt a proposed criterion function called separable distance to improve the discriminative power of an HMM. The methods are applied to identify confusable visemes. Experimental results indicate that higher recognition accuracy can be attained using these approaches than that using conventional HMM." @default.
- W2485890286 created "2016-08-23" @default.
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- W2485890286 date "2009-01-01" @default.
- W2485890286 modified "2023-09-28" @default.
- W2485890286 title "Hidden Markov Model Based Visemes Recognition, Part II" @default.
- W2485890286 cites W2077574412 @default.
- W2485890286 doi "https://doi.org/10.4018/978-1-60566-186-5.ch012" @default.
- W2485890286 hasPublicationYear "2009" @default.
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