Speaker Identification and Verification System for Arabic and Berber Language

The purpose of this work is to explore the advantage of Mel Frequency Cepstral Coefficients and Linear Predictive Coding combined with Principal Component Analysis, for speaker identification system applied for Arabic and Algerian Berber language. For this aim, the multilayer perception classifier is applied where different training functions are used for recognition process to improve the global efficiency. Dynamic time wrapping (DTW) is also applied for speaker verification. A Comparative analysis with some methods reveals that the proposed method provide good efficiency for verification and identification.