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This paper reports a word modeling algorithm for the Malayalam isolated digit recognition to reduce the search time in the classification process. A recognition experiment is carried out for the 10 Malayalam digits using the Mel Frequency Cepstral Coefficients (MFCC) feature parameters and k - Nearest Neighbor (k-NN) classification algorithm. A word modeling schema using Hidden Markov Model (HMM) algorithm is developed. From the experimental result it is reported that we can reduce the search time for the classification process using the proposed algorithm in telephony application by a factor of 80% for the first digit recognition.

Search Time Reduction Using Hidden Markov Models for Isolated Digit Recognition