Applying Physiologically-Motivated Models of Auditory Processing to Speech
The Department of Cognitive Sciences and the Center for Hearing Research present:
"Applying Physiologically-Motivated Models of Auditory Processing to Automatic Speech
Recognition: Promise, Progress, and Problems"
with Richard M. Stern, Professor, Department of Electrical and Computer Engineering
and Language Technologies Institute, Carnegie Mellon University
Thursday, April 9, 2009
12:00 p.m.
Social Science Plaza A, Room 2112
About the talk:
For many years the human auditory system has been an inspiration for developers of
automatic speech recognition systems because of its ability to interpret speech accurately
in a wide variety of difficult acoustical environments. This talk will discuss the
application of physiologically-motivated and psychophysically-motivated approaches
to signal processing that facilitates robust automatic speech recognition. The talk
will begin by reviewing selected aspects of auditory processing that are believed
to be especially relevant to speech perception, and that had been components of signal
processing schemes that were proposed in the 1980s. Stern will review and discuss
the motivation for, and the structure of, classical and contemporary computational
models of auditory processing that have been applied to speech recognition, and evaluate
and compare their impact on improving speech recognition accuracy. Finally, Stern
will discuss some of the reasons why he believes that progress to date has been limited,
and speculate on especially promising arenas for future research.
About the speaker:
Richard M. Stern received the S.B. degree from the Massachusetts Institute of Technology
in 1970, the M.S. from the University of California, Berkeley, in 1972, and the Ph.D.
from MIT in 1977, all in electrical engineering. He has been on the faculty of Carnegie
Mellon University since 1977, where he is currently a Professor in the Electrical
and Computer Engineering, Computer Science, and Biomedical Engineering Departments,
the Language Technologies Institute, and the School of Music. Much of Dr. Stern''s
current research is in spoken language systems, where he is particularly concerned
with the development of techniques with which automatic speech recognition can be
made more robust with respect to changes in environment and acoustical ambience. He
has also developed sentence parsing and speaker adaptation algorithms for earlier
CMU speech systems. In addition to his work in speech recognition, Dr. Stern has worked
extensively in psychoacoustics, where he is best known for theoretical work in binaural
perception. Dr. Stern is a Fellow of the Acoustical Society of America, the 2008-2009
Distinguished Lecturer of the International Speech Communication Association, a recipient
of the Allen Newell Award for Research Excellence in 1992, and he served as General
Chair of Interspeech 2006. He is also a member of the IEEE and the Audio Engineering
Society.
For further information, please contact Jayne Lee, 949.824.3771.
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