Hierarchical K-Means Algorithm Applied On Isolated Malay Digit Speech Recognit ion

In recent years, there has been an increasing interest in speech recognition in terms of accuracy. In this paper, the implementation of a speech recognition system in a speaker-independent isolated Malay digit was discussed. The system is developed applying Hierarchical K-means clustering approach that combines the K-means and the Hierarchical algorithm. To recognize the Malay speech digits, the Mel Frequency Cepstral Coefficient technique (MFCC) is used to extract speech features, Hierarchical K-means used as a clustering technique for training and testing of the feature's vectors. The performance of the system was evaluated. And the overall speech recognition accuracy attained 87.5% which is considerably satisfactory. Keyw ords: Clustering, Hie rarchical K-Means, MFCC, Speech Recognition

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