The Hidden Markov Model of Co-articulation and Its Application to the Continuous Speech Recognition
نویسندگان
چکیده
Abstract the co-articulation is one of the main reasons that makes the speech recognition difficult. However, the traditional Hidden Markov Models(HMM) can not model the co-articulation, because they depend on the first-order assumption. In this paper, for modeling the co-articulation, we propose a more perfect HMM than traditional first order HMM on the basis of our previous works and they give a method in that this HMM is used in continuous speech recognition by means of multilayer perceptrons (MLP), i.e. the hybrid HMM/MLP method with triple MLP structure. The experiment we conduct shows that this new hybrid HMM/MLP method decreases error rate in comparison with our previous works.
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