Abstract
An algorithm for recognition in continuous speech is presented. A continuous matching process is employed to bypass the segmentation problem. A large set of standard patterns is used to solve the allophonic variation problem. Also, a hierarchical recognition algorithm is proposed to realize feasible matching in a real time. In the first stage of the hierarchical recognition algorithm, vowels in speech are spotted. To optimize accuracy in vowel spotting, each standard pattern is carefully selected, constraints on the phoneme chain of continuous speech are utilized, and partial standard pattern matching is employed for detailed analysis. The second stage recognizes consonants between vowels. Experimental results show a 91% vowel recognition rate and 80% consonant recognition rate for a specified speaker.
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