Hidden Markov Model-Based Modelling of Context-Dependent Phonemes Using Decision Tree-Based State Clustering
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چکیده
This paper discusses hidden Markov model-based context-dependent phoneme modelling and their associated problems, particulary data insufficiency and unseen triphones. The implementation of decision tree-based state clustering, a technique suitable for solving these problems, is discussed. This technique was first proposed in 1994 by Young, Woodland and Odell [1]. A triphone-based phoneme recognition system, constructed using decision tree-based state clustering, is compared to a baseline monophone-based recognition system.
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تاریخ انتشار 2002