By Topic

Voice as a Robust Biometrics

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
$33 $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

2 Author(s)
Yushi Zhang ; Dept. of Electr. & Comput. Eng., Univ. of Auckland, Auckland, New Zealand ; Abdulla, W.H.

Robust voice based features for biometric authentication in noisy environments are proposed. The proposed processing includes gamma tone auditory bandpass filtering of speech signal, rectification, and compression to model the effects of the auditory system periphery. Three features are extracted by applying independent component analysis to the frequency, cepstral and auto-correlogram domains of the compressed output signals respectively. A specially prepared noisy speech corpus was used to gauge the performance of the proposed features on a speaker identification system. Experimental results show that these features can well denote the distribution of speakers and are robust to background noises compared with the traditional features, such as LPCC, MFCC and PLP. Among the proposed features, the feature extracted in auto-correlogram domain achieves the best identification performance in noisy-mismatched environments.

Published in:

Future Generation Communication and Networking, 2008. FGCN '08. Second International Conference on  (Volume:3 )

Date of Conference:

13-15 Dec. 2008