A new dynamic HMM (hiddem Markov model) has been introduced in this paper, which describes the relationship between dynamic property and feature of space. The method to estimate the dynamic property is discussed in this paper, which makes the dynamic HMMmuch more practical in real time speech recognition. Ex-periment on large vocabulary continuous Mandarin speech recognition task has shown that the dynamic HMM model can achieve about 10% of error reduction both for tonal and toneless syllable. Estimated dynamic property can achieve nearly same (even better) performance than using extracted dynamic property.
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