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

Linear trajectory models incorporating preprocessing parameters for 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

1 Author(s)
Chengalvarayan, R. ; Lucent Technol., Bell Labs., Naperville, IL, USA

In this letter, we investigate the interactions of front-end feature extraction and back-end classification techniques in nonstationary state hidden Markov model (NSHMM) based speech recognition. The proposed model aims at finding an optimal linear transformation on the mel-warped discrete Fourier transform (DFT) features according to the minimum classification error (MCE) criterion. This linear transformation, along with the NSHMM parameters, are automatically trained using the gradient descent method. An error rate reduction of 8% is obtained on a standard 39-class TIMIT phone classification task in comparison with the MCE-trained NSHMM using conventional preprocessing techniques.

Published in:

Signal Processing Letters, IEEE  (Volume:5 ,  Issue: 3 )

Date of Publication:

March 1998

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.