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

Scaling down: applying large vocabulary hybrid HMM-MLP methods to telephone recognition of digits and natural numbers

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)
Ma, K. ; Int. Comput. Sci. Inst., Berkeley, CA, USA ; Morgan, N.

The hybrid hidden Markov model (HMM)/neural network (NN) speech recognition system at the International Computer Science Institute (ICSI) uses a single hidden layer multilayer perceptron (MLP) to compute emission probabilities of HMM states. This phoneme-based recognition approach was developed for large vocabulary size continuous speech recognition. In this paper, however, such a recognition scheme is applied directly to much smaller vocabulary size corpora, such as the Spoken Language Understanding Numbers'93 database and the TI connected digits. The authors report on the development of small baseline systems to facilitate all future research experiments, and also on the use of these systems for experiments in context-dependent hybrid HMM-MLP systems

Published in:

Neural Networks for Signal Processing [1995] V. Proceedings of the 1995 IEEE Workshop

Date of Conference:

31 Aug-2 Sep 1995

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.