Boltzmann Machine Neural Network for Arabic Speech Recognition

Boltzmann machine neural network has been used to recognize the Arabic speech. Fast Fourier transformation algorithm has been used to extract spectral features from an a coustic signal. The spectral feature size is reduced by scries of operations in order to make it salable as input for a neural network which is used as a recogni/.er by Boltzmann Machine Neural network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme rcpesentations, is used to train the neural network. The neural network recognized Arabic. After Boltzmann Machinc Neural network training the system with few selected Arabic phonemes, the results came out to be very encouraging .