GFIS: Genetic Fuzzy Inference System for Speech Recognition

Washington Luis Santos Silva, Ginalber Luiz de Oliveira Serra


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.


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Paper Citation

in Harvard Style

Luis Santos Silva W. and Serra G. (2012). GFIS: Genetic Fuzzy Inference System for Speech Recognition . In Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO, ISBN 978-989-8565-21-1, pages 536-541. DOI: 10.5220/0004045705360541

in Bibtex Style

author={Washington Luis Santos Silva and Ginalber Luiz de Oliveira Serra},
title={GFIS: Genetic Fuzzy Inference System for Speech Recognition},
booktitle={Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,},

in EndNote Style

JO - Proceedings of the 9th International Conference on Informatics in Control, Automation and Robotics - Volume 1: ICINCO,
TI - GFIS: Genetic Fuzzy Inference System for Speech Recognition
SN - 978-989-8565-21-1
AU - Luis Santos Silva W.
AU - Serra G.
PY - 2012
SP - 536
EP - 541
DO - 10.5220/0004045705360541