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

Closely Coupled Array Processing and Model-Based Compensation for Microphone Array 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)
Xianyu Zhao ; Dept. of Electron. Eng., Tsinghua Univ., Beijing ; Zhijian Ou

In conventional microphone array speech recognition, the array processor and the speech recognizer are loosely coupled. The only connection between the two modules is the enhanced target signal output from the array processor, which then gets treated as a single input to the recognizer. In this approach, useful environmental information, which can be provided by the array processor and also needs to be exploited by the recognizer, is ignored. Inherently, the array processor can generate multiple outputs of spatially filtered signals, as a multi-input-multi-output (MIMO) module. In this paper, a closely coupled approach is proposed, in which a recognizer with model-based noise compensation exploits the reference noise outputs from a MIMO array processor. Specifically, a multichannel model-based noise compensation is presented, including the compensation procedure using the vector Taylor series (VTS) expansion and parameter estimation using the expectation-maximization (EM) algorithm. It is also shown how to construct MIMO array processors from conventional beamformers. A number of practical implementations of the conventional loosely coupled approach and the proposed closely coupled approach were tested on a publicly available database, the Multichannel Overlapping Number Corpus (MONC). Experimental results showed that the proposed closely coupled approach significantly improved the speech recognition performance in the overlapping speech situations

Published in:

Audio, Speech, and Language Processing, IEEE Transactions on  (Volume:15 ,  Issue: 3 )

Date of Publication:

March 2007

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.