By Topic

Maximum mutual information speaker adapted training with semi-tied covariance matrices

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)
McDonough, J. ; Interactive Syst. Labs., Karlsruhe Univ., Germany ; Waibel, Alex

We present re-estimation formulae for semi-tied covariance (STC) transformation matrices based on a maximum mutual information (MMI) criterion. These re-estimation formulae are different from those that have appeared previously in the literature. Moreover, we present a positive definiteness criterion with which the regularization constant present in all NMI re-estimation formulae can be reliably set to provide both consistent improvements in the total mutual information of the training set, as well as fast convergence. We combine the STC re-estimation formulae with their like for speaker-independent means and variances, and update all parameters during NMI speaker adapted training (MMI-SAT). We present the results of two sets of speech recognition experiments conducted on the the 1998 Broadcast News evaluation set, as well as a corpus of meeting room data collected at the Interactive Systems Laboratories of the Carnegie Mellon University.

Published in:

Acoustics, Speech, and Signal Processing, 2003. Proceedings. (ICASSP '03). 2003 IEEE International Conference on  (Volume:1 )

Date of Conference:

6-10 April 2003