NDLI: A Word-Dependent Automatic Arabic Speaker Identification System

Content Provider	IEEE Xplore Digital Library
Author	Al-Dahri, S.S. Al-Jassar, Y.H. Alotaibi, Y.A. Alsulaiman, M.M. Abdullah-Al-Mamun, K.
Copyright Year	2008
Description	Author affiliation: Dept. of Comput. Eng. Dept., King Saud Univ., Riyadh (Al-Dahri, S.S.; Al-Jassar, Y.H.; Alotaibi, Y.A.; Alsulaiman, M.M.; Abdullah-Al-Mamun, K.)
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.
Starting Page	198
Ending Page	202
File Size	3052885
Page Count	5
File Format	PDF
ISBN	9781424435548
DOI	10.1109/ISSPIT.2008.4775669
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2008-12-16
Publisher Place	Serbia
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Speaker recognition Natural languages Biometrics Automatic speech recognition Speech processing Signal processing Fingers Retina Speech recognition User interfaces HMM Arabic Speaker Identification Word-dependent
Content Type	Text
Resource Type	Article

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1	Ministry of Education (GoI), Department of Higher Education	Sanctioning Authority	https://www.education.gov.in/ict-initiatives
2	Indian Institute of Technology Kharagpur	Host Institute of the Project: The host institute of the project is responsible for providing infrastructure support and hosting the project	https://www.iitkgp.ac.in
3	National Digital Library of India Office, Indian Institute of Technology Kharagpur	The administrative and infrastructural headquarters of the project	Dr. B. Sutradhar bsutra@ndl.gov.in
4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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