Abstract
This paper deals with the development of a speech recognition system and comparative study of recognition results for Bangla phonemes. At first, Phonemes were recorded and converted into digital form. Then MFCC features from phonemes were extracted by Mel scale cepstral analysis. The recognition tools include Hamming and Euclidean distance measurement and learning through a neural network. Ten Bangla phonemes were used to test the system. The performance of the system shows that Euclidean distance measurement is the simplest and better method in recognizing Bangla phonemes.
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