Automatic Speaker Identification System for Urdu Speech

FATIMA YOUSAF, Min Peng, Samia Razaq, Agha Ali Raza, Suleman mazhar, qianqian Xie, Dong Li


Speaker recognition is the process of recognizing a speaker from a verbal phrase. Such systems generally operates in two ways: to identify a speaker or to verify speaker’s claimed identity. Availability of valuable research material witnessed efforts paid to Automatic Speaker Identification (ASI) in East Asian, English and European languages. But unfortunately languages of South Asia especially “Urdu” have got very less attention. This paper aims to describe a new feature set for ASI in Urdu speech, achieving improved performance than baseline systems. Classifiers like Neural Net, Naïve Bayes and K nearest neighbor (K-NN) have been used for modeling. Results are provided on the dataset of 40 speakers with 82% correct identification. Lastly, improvement in system performance is also reported by changing number of recordings per speaker.

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Chief Editor

Prof. Dr. Ejaz Ahmed 
College of Computer Science & Information Systems


Prof Dr. S. M. Aqil Burney

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Dr. Muhammad Mansoor Aalam

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Dr. Mohammad Irshad Khan
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Prof. Dr. Ghassan Al-Qaimari, President, Emirates College of Technology, Abu Dhabi, UAE
Prof. Dr. Patrice Boursier, Universite de La Rochelle, La Rochelle, France
Prof. Dr. Mudassir Uddin, Professor, University of Karachi, Pakistan
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