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

Subband Feature Statistics Normalization Techniques Based on a Discrete Wavelet Transform for Robust Speech 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)
Jeih-weih Hung ; Dept. of Electr. Eng., Nat. Chi Nan Univ., Nantou, Taiwan ; Hao-Teng Fan

This letter proposes a novel scheme that applies feature statistics normalization techniques for robust speech recognition. In the proposed approach, the processed temporal-domain feature sequence is first decomposed into nonuniform subbands using the discrete wavelet transform (DWT), and then each subband stream is individually processed by well-known normalization methods, such as mean and variance normalization (MVN) and histogram equalization (HEQ). Finally, we reconstruct the feature stream with all of the modified subband streams using the inverse DWT. With this process, the components that correspond to more important modulation spectral bands in the feature sequence can be processed separately.

Published in:

Signal Processing Letters, IEEE  (Volume:16 ,  Issue: 9 )

Date of Publication:

Sept. 2009

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.