A hybrid approach based on DCT-Genetic-Fuzzy inference system for speech recognition

Authors:
Washington Silva;Ginalber Serra
Affiliations:
Department of Electroelectronics, Laboratory of Computational Intelligence Applied to Technology, Federal Institute of Education, Science and Technology, São Luis, Maranhão, Brazil;Department of Electroelectronics, Laboratory of Computational Intelligence Applied to Technology, Federal Institute of Education, Science and Technology, São Luis, Maranhão, Brazil
Venue:
IDEAL'12 Proceedings of the 13th international conference on Intelligent Data Engineering and Automated Learning
Year:
2012

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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 Hybrid DCT-Genetic-Fuzzy Inference System for Speech Recognition (HGFIS) .