A novel intelligent system for speech recognition

Abstract

The concept of fuzzy sets and fuzzy logic is widely used to propose several methods applied to modeling, classification and pattern recognition problem. This paper proposes an Intelligent Methodology for Speech Recognition (IMSR). 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 algorithm is used to optimize a Mamdani fuzzy inference system in order to obtain the best model with minimum number of parameters for final recognition. 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.