San Francisco State University
Computer ScienceDOD funds speech recognition project
Reproduced with permission from NeXT
Computer, Inc.
A Reference
Guide to NeXT in Higher Education, Fall 1992
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1992 NeXT Computer,
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Thomas Holton, associate
professor of engineering, and two undergraduate computer
science students, Joel Miller and Lee Worden, are using
models of auditory signal processing to develop improved
algorithms for the computer recognition of speech. The
entire project, which is funded by the Department of
Defense, is taking place on NeXT machines, using the
graphics and DSP functions extensively.
"The purpose of our work," says Holton, "is to understand
the fundamental strategy used by the auditory system to
process speech signals and to apply this understanding to
the design of improved algorithms for robust computer
recognition of speech features."
According to Holton, "My background is in hearing,
experimental neuropsychology and electrical engineering,
and this project combines my interests in these areas. The
project also reflects my philosophical feeling that speech
is a fundamentally human activity, and that current
engineering approaches to speech recognition-e.g.
spectrographic approaches-do not process speech the way
humans do. In fact, our approach shows significant promise
compared to the conventional spectrographically based
algorithms."
In collaboration with colleagues Steve Love and Steve Gill
of Votan Corporation, Holton has developed a comprehensive
model of peripheral and early central auditory signal
processing. The components include a detailed
three-dimensional hydro-mechanical model of the cochlea,
which describes the fluid-wave processes underlying
basilar-membrane motion, a biophysical description of
mechano-electric transduction in cochlear hair cells, a
description of the time-dependent synaptic chemistry of
hair cells and auditory-nerve fibers, and a
`micro-neural-net' description of neural signal processing
in the cochlear nucleus.
"A comparison of the predictions of the model with
experimental physiological data obtained in response to
simple (tonal) and complex (speech) stimuli suggests that
the model accurately describes essential features of
auditory signal processing," says Holton.
The researcher says he purchased the NeXT machines for the
project because they had "the right mix of features at a
reasonable price."
"The auditory-model algorithms that form the core of our
approach are highly DSP-intensive, and the DSP56001
co-processor in the NeXT was initially a strong selling
point," he explains. "The applications we've written also
require sound recording, editing and playback, and
high-resolution displays. The PostScript display capability
of the NeXT machine, as well as NeXT's development
environment and set of supplied objects (e.g. SoundKit)
have been instrumental in helping us get our applications
up and running fast, and helping us maintain them."
For more information, please contact:
Thomas Holton
Associate Professor of Engineering
San Francisco State University
1600 Holloway Avenue
San Francisco, CA 94132
(415) 338-1529
th@ernie.sfsu.edu