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

Speaker-adaptation in a hybrid HMM-MLP recognizer

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

3 Author(s)
Neto, J.P. ; INESC, Lisbon, Portugal ; Martins, C. ; Almeida, L.B.

Presently the most important systems for large vocabulary, continuous speech recognition are speaker-independent. These systems deal with the inter-speaker variability through a large pool of speakers. However, this approach has several drawbacks due to its inability to cope with the individual speaker characteristics. The problem is more extreme for the cases of fast or non-native speakers. In this paper we present a technique for speaker-adaptation in the context of a hybrid HMM-MLP system for large vocabulary, speaker-independent, continuous speech recognition. This technique is implemented both in supervised and unsupervised modes. In the unsupervised case both static and incremental approaches are explored. The results show that speaker-adaptation within the hybrid HMM-MLP framework can substantially improve system performance. In the incremental unsupervised mode, the improvement is obtained without any extra demands on the speaker, i.e. without an enrolment phase

Published in:

Acoustics, Speech, and Signal Processing, 1996. ICASSP-96. Conference Proceedings., 1996 IEEE International Conference on  (Volume:6 )

Date of Conference:

7-10 May 1996

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.