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

Shared-distribution hidden Markov models 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

2 Author(s)
Hwang, M.-Y. ; Sch. of Comput. Sci., Carnegie Mellon Univ., Pittsburgh, PA, USA ; Xuedong Huang

A shared-distribution hidden Markov model (HMM) is presented for speaker-independent continuous speech recognition. The output distributions across different phonetic HMMs are shared with each other when they exhibit acoustic similarity. This sharing provides the freedom to use a larger number of Markov states for each phonetic model. Although an increase in the number of states will increase the total number of free parameters, with distribution sharing one can collapse redundant states while maintaining necessary ones. The shared-distribution model reduced the word error rate on the DARPA Resource Management task by 20% in comparison with the generalized-triphone model

Published in:

Speech and Audio Processing, IEEE Transactions on  (Volume:1 ,  Issue: 4 )

Date of Publication:

Oct 1993

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.