Authors:
Washington Luis Santos Silva
and
Ginalber Luiz de Oliveira Serra
Affiliation:
Federal Institute of Education and Science and Technology, Brazil
Keyword(s):
Recognition Speech, Fuzzy Systems, Optimization, Genetic Algorithm, Discrete Cosine Transform.
Related
Ontology
Subjects/Areas/Topics:
Engineering Applications
;
Informatics in Control, Automation and Robotics
;
Intelligent Control Systems and Optimization
;
Optimization Problems in Signal Processing
;
Robotics and Automation
;
Signal Processing, Sensors, Systems Modeling and Control
Abstract:
The concept of fuzzy sets and fuzzy logic is widely used to propose of several methods applied to systems
modeling, classification and pattern recognition problem. This paper proposes a genetic-fuzzy recognition
system for speech recognition. In addition to pre-processing, with mel-cepstral coefficients, the Discrete Cosine
Transform (DCT) is used to generate a two-dimensional time matrix for each pattern to be recognized.
A genetic algorithms is used to optimize a Mamdani fuzzy inference system in order to obtain the best model
for final recognition. The speech recognition system used in this paper was named Genetic Fuzzy Inference
System for Speech Recognition (GFIS). Experimental results for speech recognition applied to brazilian language
show the efficiency of the proposed methodology compared to methodologies widely used and cited in
the literature.