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In this paper we propose an approach that aims to build an automated task-oriented Arabic dialogue system which is capable to determine the topic of spoken question asked by telecom provider customers. The system is based on an Arabic adapted CMU sphinx ASR. In addition to formal Arabic speech, our implemented Arabic ASR is capable to recognize some(More)
Abstract—Automatic identification of speech disorders in children’s speech is very important for the diagnosis and monitoring of speech therapy. In this work, acoustic features (MFCC) have been used with the two most commonly used classification techniques in the speaker and language identification area, GMM-UBM and I-vector, for identifying three error(More)
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