BISC SEMINAR 2/22


Subject: BISC SEMINAR 2/22
From: cindy mason (cmason@cs.berkeley.edu)
Date: Sat Feb 19 2000 - 00:18:48 MET


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Berkeley Initiative in Soft Computing (BISC)
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BISC SEMINAR

     310 Soda Hall
     Tuesday, Feburary, 1st, 2000
     4pm-5pm
   
     Expressive Probability Models for Speech Recognition and
 Understanding
     =========================================

     Stuart Russell

     Computer Science Division
     University of California at Berkeley
     Berkeley, CA 94720, USA
     eMail: russell@cs.berkeley.edu

     ABSTRACT: This talk summarizes a recent foray into speech
 recognition. The
 principal points are as follows: first, that the expressive power of
 the probability models available for use in speech recognition and
 understanding has expanded significantly; second, that using
 expressive models such as dynamic Bayesian networks can result in
 improved learning rates and recognition results; and finally that
 still further expansion is required to tackle many problems of
 interest in the area of speech understanding. This further expansion
 should combine probability theory with the expressive power of
 first-order logical languages. An approximate inference method is
 outlined for representation systems of this kind.

 (Part of this talk describes joint work with Geoff Zweig)

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