Proposal of an Intelligent Speech Recognition System

Author

Silva, Washington Luis Santos ; de Oliveira Serra, Ginalber Luiz

Author_Institution

Lab. of Eletronics Instrum., Fed. Inst. of Maranhao-IFMA, Säo Luis, Brazil

fYear

2012

fDate

6-8 Nov. 2012

Firstpage

356

Lastpage

359

Abstract

The concept of fuzzy sets and fuzzy logic is widely used to proposal of several methods applied to systems modeling, classification and pattern recognition problem. This paper proposes a genetic-fuzzy system for extraction of low-order features for speech recognition application. In addition to pre-processing, with mel-cepstral coefficients, the Discrete Cosine Transform (DCT) is used to generate a two-dimensional time matrix with the features of low-order 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 for final recognition.

Keywords

cepstral analysis; discrete cosine transforms; fuzzy logic; fuzzy reasoning; fuzzy set theory; genetic algorithms; signal classification; speech recognition; DCT; Mamdani fuzzy inference system; classification; discrete cosine transform; fuzzy logic; fuzzy set; genetic algorithm; genetic-fuzzy system; intelligent speech recognition system; low-order feature extraction; mel-cepstral coefficient; pattern recognition problem; systems modeling; two-dimensional time matrix; Discrete cosine transforms; Genetic algorithms; Hidden Markov models; Speech; Speech recognition; Training; Discrete Cosine Transform; Fuzzy Systems; Genetic Algorithm; Speech Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Intelligent Systems (GCIS), 2012 Third Global Congress on

Conference_Location

Wuhan

Print_ISBN

978-1-4673-3072-5

Type

conf

DOI

10.1109/GCIS.2012.106

Filename

6449553