Abstract
Arabic language is a semantic language that has complicated difficulties when compared to English and other languages. In this paper an Arabic speaker recognition system has been developed for introducing conversion of the uttered Arabic speaker instantly after the utterance. The voice samples were recorded, the pre-processing activity detected to evaluate the voice parts from unvoiced, framing and rectangular window slides techniques has been used for segmentation of the Arabic Speech signals, followed by Mel Frequency Spectrum Coefficients (MFCC) for features extractions, The feature vectors are grouped for each spoken sample using VQLBG Algorithm and Gaussian Mixer Model (GMM) applied for classification and recognition an unknowing speaker through his uttered words which belong to specific cluster that is differenced form others clusters related to others Arabic speakers. This approach reported in providing 95.5% of recognition rate.
Highlights
Arabic is a semantic language that has complicated difficulties when compared to English language
Some of the difficulties encountered by a speech recognition system that are related to the Arabic language are fully described in literature references such as in [1],[2],[15],[41],[42]
By checking the voice characteristics of the input utterance, using an automatic speaker recognition system similar to the one that this paper describe, the system is able to add an extra level of security and other applications
Summary
Arabic is a semantic language that has complicated difficulties when compared to English language. Some of the difficulties encountered by a speech recognition system that are related to the Arabic language are fully described in literature references such as in [1],[2],[15],[41],[42]. Lack of spoken and written training data is one of the main issues encountered by Arabic ASR researchers. These problems can be minimized by restricting the number of speakers, words and working with good acoustic condition. Arabic speaker recognition have important application in daily life, there is a need for controlled access to certain information or places for security. The topic of this paper deals with speaker recognition that refers to the task of recognizing people by their voices[20],[22].
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