Recognizing Arabic letter utterance using convolutional neural network

Arabic letters have unique characteristics because of similarity of sound produced when reciting few letters. This paper present one of application Convolutional Neural Network (CNN) in speech recognition Arabic letters. CNN has shown very good performance for image and speech recognition int the last few years. This study examined the several types of CNN models as well as compare with some Deep Neural Network (DNN) models to speech datasets used. As a result, CNN with a convolution layer and one layer fully-connected managed to obtain an accuracy of up to 80.75%, far better than the traditional DNN that only able to reach 72.0%.