A Word-Dependent Automatic Arabic Speaker Identification System

Abstract

Automatic speaker recognition is one of the difficult tasks in the field of computer speech and speaker recognition. Speaker recognition is a biometric process of automatically recognizing who is speaking on the basis of speaker dependent features of the speech signal. Currently, speaker recognition system is an important need for authenticating the personal like other biometrics such as finger prints and retinal scans. Speech based recognition permits both on site and remote access to the user. In this research, speaker identification system is investigated from the speaker recognition problem point of view. It is an important component of a speech-based user interface. The aim of this research is to develop a system that is capable of identifying an individual from a sample of his or her speech. Arabic language is a semitic language that differs from European languages such as English. Our system is based on Arabic speech. We have chosen to work on a word-dependent system using the Arabic isolated word /ns10 as10 cs10 as10 ms10//[unk]/ a single keyword for the test utterance. This choice has been made because the word /ns10 as10 cs10 as10 ms10//[unk]/ is mostly used by the Arabic speakers. Speech features are extracted using MFCC. The HTK is used to implement the speaker identification module with phoneme based HMM. The designed automatic Arabic speaker identification system contains 100 speakers and it achieved 96.25% accuracy for recognizing the correct speaker.