Boltzmann Machine Neural Network for Arabic Speech Recognition - Mohamed, H.R (Ibn AL-Haitham Journal For Pure and Applied Sciences, 2017)
Boltzmann mach ine neural network bas been used to recognize the Arabic speech. Fast Fourier transl(>lmation algorithm has been used t() extract speciral ’features from an a caustic signal . The spectral feature size is reduced by series of operations in order to make it salable as input for a neural network which is used as a recogni zer by Boltzmann Machine Neural network which has been used as a recognizer for phonemes . A training set consist of a number of Arabic phoneme repesentations, is used to train lhe neuntl network. The neural network recognized Arabic. After Boltzmann Machine Neura l network training the system with few selected Arabic phonemes, the results came out to be very encouragi ng .