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A word-class bigram statistics language model supported by a huge Chinese lexicon of 87,326 word entries has been investigated on its effectiveness in upgrading the accuracy of a hand-written Chinese character recognizer. The concept of the homogeneity of a word-class is introduced in classifying words into word-classes. On the average, the bigram statistics language model upgrades the recognition...
In this paper, by using the formulation of the missing-data problem, a general framework for statistical acoustic modelling of speech is presented. With the motivation of utilizing bi-directional contextual dependence in acoustic modelling, a bi-directional hidden Markov modelling approach for speech recognition is studied and the importance of the bi-directional contextual dependence for speech recognition...
By using formulation of the finite mixture distribution identification, in this paper, several alternatives to the conventional LBG VQ method are investigated. A contextual VQ method based on the Markov Random Field (MRF) theory is proposed to model the speech feature vector space. Its superiority is confirmed by a series of comparative experiments in a speaker independent isolated word recognition...
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