By Topic

Forensic Identification Reporting Using A GMM Based Speaker Recognition System Dedicated to Algerian Arabic Dialect Speakers

Sign In

Cookies must be enabled to login.After enabling cookies , please use refresh or reload or ctrl+f5 on the browser for the login options.

Formats Non-Member Member
$31 $13
Learn how you can qualify for the best price for this item!
Become an IEEE Member or Subscribe to
IEEE Xplore for exclusive pricing!
close button

puzzle piece

IEEE membership options for an individual and IEEE Xplore subscriptions for an organization offer the most affordable access to essential journal articles, conference papers, standards, eBooks, and eLearning courses.

Learn more about:

IEEE membership

IEEE Xplore subscriptions

4 Author(s)
Bengherabi, M. ; Centre de Dev. des Technol. Av., Algiers ; Tounsi, B. ; Bessalah, H. ; Harizi, F.

Starting from the fact of the lack of Arabic databases dedicated to performance evaluation of speaker recognition and forensic reporting systems. We present in this paper our experience in constructing an Algerian dialect database and the motivation beyond this work. After that, the corpus based Bayesian framework for interpretation of evidence in forensic systems in terms of likelihood ratio (LR) is applied on this database under different recording conditions: microphone, fixed and cellular. Preliminary results in terms of Receiver Operating Characteristics (ROC) and TIPPET plots show higher accuracy in matched conditions of training and testing. However, the performance degrades significantly in mismatched conditions.

Published in:

Information and Communication Technologies: From Theory to Applications, 2008. ICTTA 2008. 3rd International Conference on

Date of Conference:

7-11 April 2008