A hybrid approach based on DCT-genetic-fuzzy inference system for speech recognition

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). © 2012 Springer-Verlag.