By Topic

Robust speaker identification using auditory features and computational auditory scene analysis

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)
Yang Shao ; Department of Computer Science and Engineering, The Ohio State University Columbus, 43210-1277, USA ; DeLiang Wang

The performance of speaker recognition systems drop significantly under noisy conditions. To improve robustness, we have recently proposed novel auditory features and a robust speaker recognition system using a front-end based on computational auditory scene analysis. In this paper, we further study the auditory features by exploring different feature dimensions and incorporating dynamic features. In addition, we evaluate the features and robust recognition in a speaker identification task in a number of noisy conditions. We find that one of the auditory features performs substantially better than a conventional speaker feature. Furthermore, our recognition system achieves significant performance improvements compared with an advanced front-end in a wide range of signal-to-noise conditions.

Published in:

2008 IEEE International Conference on Acoustics, Speech and Signal Processing

Date of Conference:

March 31 2008-April 4 2008