Fast Likelihood Computation Method Using Block-diagonal Covariance Matrices in Hidden Markov Model
نویسندگان
چکیده
The paper presented a novel method to speed up the likelihood computation of the speech recognition system based continuous Hidden Markov Model (CHMM). The block-diagonal covariance matrices were applied in the method and the technique to construct an optimal block-diagonal matrix was introduced. The experimental results demonstrated that the block-diagonal covariance matrices could achieve a large improvement in recognition speed without significant decrease of recognition rate compared with baseline system.
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تاریخ انتشار 2002