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Recognition of isolated words in Bulgarian, by means of HMM

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3 Author(s)
S. Hadjitodorov ; Dept. of Electr. Eng., Manitoba Univ., Winnipeg, Man., Canada ; B. Boyanov ; B. Rahardjo

The problem of the recognition of Bulgarian words by means of HMM (hidden Markov models) is discussed. The speech signal was low-pass filtered up to 4 kHz, sampled at 10 kHz, and pushed directly into the computer's memory (IBM PC/XT). Unvoiced segments were separated, and the pitch period was evaluated. For every voiced and unvoiced segment 12 LPC (linear predictive coding) coefficients were computed. These segments were used as states q/sub i/ in HMM and their LPC coefficients-an acoustic vector y/sub t/. On the basis of the training set a HMM for every word was generated. A modified Bayesian decision rule is proposed. As a result, if the decision rule is satisfied, the classification is simple; otherwise, the classification is given in the form of ordered couples. The proposed approach shows higher accuracy and is appropriate for word, command and expression recognition.<>

Published in:

Communications, Computers and Signal Processing, 1989. Conference Proceeding., IEEE Pacific Rim Conference on

Date of Conference:

1-2 June 1989