Fuzzy Logic

Fuzzy Speech Recognition
Masters Thesis
Abstract
Speech recognition allows for
extremely efficient man-machine communication. Since most computers are
used to interactively input or output data, communication by speech
represents the ideal computer interface. Recognition requires
intelligence, and is, therefore, a much more difficult problem than
speech production. While general speech recognition is a daunting task,
a much simpler system would still be useful. This thesis presents a
simple speech recognition system that can be implemented with a personal
computer and a sound card. Once a limited system has been implemented,
its capabilities can be scaled by using faster computers and specialized
hardware as necessary.
Fuzzy logic allows effective decision
making in the presence of uncertainty. Identifying spoken words, even in
an ideal environment by a trained speaker, is a complex task filled with
uncertainty. The speech waveform is nonlinear and variant, removing the
possibility of simple analysis. However, by analyzing the waveform for
reoccurring and semi-stable features, small segments may be classified.
A fuzzy expert may then make decisions based on these features to
identify the spoken word. The identification represents the decision
that the chosen word is present and also that other words are not
present. Furthermore, the system's confidence in its identification can
be used to accept the identification or to request further information or
help.
This thesis is available as a
PDF file (622K).
Fuzzy Logic Enhanced Symmetric Dynamic Programming for Speech Recognition
5th IEEE International Conference on Fuzzy Systems
Abstract
Fuzzy logic allows effective decision making in the presence of
uncertainty. Identifying spoken words, even in an ideal environment by a
trained speaker, is a complex task filled with uncertainty. The speech
waveform is nonlinear and variant, removing the possibility of simple
analysis. Dynamic programming is a time normalization technique that
allows static templates to be used to identify spoken words. Fuzzy logic
enhancements enable the technique to handle noise and quantization errors
better and improves classification accuracy. An important consequence of
using a fuzzy based system is that the system's confidence in its
identification can be used to accept the identification or to request
further information.
A Fuzzy Logic Positioning System for an Articulated Robot Arm
5th IEEE International Conference on Fuzzy Systems
Abstract
Articulated robot arms offer maximum positioning flexibility but suffer
from complex kinematics. In most applications, linear motion is desirable.
Calculating the kinematic equations which govern an articulated arm is
straight forward; however, it is generally difficult to calculate the
inverse kinematic equations that are needed to position the arm in closed
form. Using a fuzzy reasoning system, it is possible to accurately
position an articulated arm without explicitly solving the inverse
kinematic equations.
Other Sites for Fuzzy Information
Togai InfraLogic, Inc.
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(Last Updated: Tuesday, 06-Jun-2000 07:07:44 EDT)
mills@nvrlnd.com - © 1996 Patrick M. Mills. All Rights Reserved.