Cart (Loading....) | Create Account
Close category search window

The integral decode: a smoothing technique for robust HMM-based speaker recognition

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

2 Author(s)
Roch, M. ; Dept. of Comput. Sci., Iowa Univ., Iowa City, IA, USA ; Hurtig, R.R.

Previous work by Merhav and Lee (1993) as well as others has emphasized that the conditions required to make the maximum a posteriori (MAP) decision rule an optimal decision rule for speech recognition do not hold and have proposed techniques based upon the adjustment of model parameters to improve speech recognition. In this article, we consider the problem of text-independent speaker recognition, and present a new model called the integral decode. The integral decode, like previous work in this area, attempts to compensate for the lack of conditions necessary to ensure optimality of the MAP decision rule in environments with corrupted observations and imperfect models. The integral decode is a smoothing operation in the feature space domain. A region of uncertainty is established about each noisy observation and an approximation of the integral is computed. The MAP decision rule is then applied to the smoothed likelihood estimates. In all tested conditions, the integral decode performs as well as or better than equivalent HMMs without integral decode.

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:10 ,  Issue: 5 )

Date of Publication:

Jul 2002

Need Help?

IEEE Advancing Technology for Humanity About IEEE Xplore | Contact | Help | Terms of Use | Nondiscrimination Policy | Site Map | Privacy & Opting Out of Cookies

A not-for-profit organization, IEEE is the world's largest professional association for the advancement of technology.
© Copyright 2014 IEEE - All rights reserved. Use of this web site signifies your agreement to the terms and conditions.