Hidden Markov Models for Labeled Sequences
نویسنده
چکیده
A hidden Markov model for labeled observations, called a CHMM, is introduced and a maximum likelihood method is developed for estimating the parameters of the model. Instead of training it to model the statistics o f the training sequences it is trained to optimize recognition, It resembles MMI training, but is more general, and has MMI as a special case. The standard forwardbackward procedure for estimating the model cannot be generalized directly, but an “incremental EM” method is proposed.
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