Boltzmann Machine Neural Network for Arabic Speech Recognition
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Abstract
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 .
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Boltzmann Machine Neural Network for Arabic Speech Recognition. (2017). Ibn AL-Haitham Journal For Pure and Applied Sciences, 19(4), 125-133 E. https://jih.uobaghdad.edu.iq/index.php/j/article/view/1679
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Computer
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How to Cite
Boltzmann Machine Neural Network for Arabic Speech Recognition. (2017). Ibn AL-Haitham Journal For Pure and Applied Sciences, 19(4), 125-133 E. https://jih.uobaghdad.edu.iq/index.php/j/article/view/1679