Study of speech analysis techniques for the phonemes classification using fuzzy logic

Author

Fredj, I.B. ; Ouni, Kaïs

Author_Institution

LSTS Lab., Tunis El Manar Univ., Tunis, Tunisia

fYear

2011

fDate

22-25 March 2011

Firstpage

1

Lastpage

5

Abstract

In this work, we study speech analysis techniques to classify phoneme using a method of fuzzy logic. The used techniques are Mel Frequency Cepstral Coefficient (MFCC), Perceptual Linear Prediction (PLP) and RelAtive SpecTrAl-Perceptual Linear Prediction (RASTA-PLP). The fuzzy logic method is characterized by three fuzzy reference vectors: the maximal vector, the mean vector and the minimal vector. To classify a phoneme request, we calculate the degree of membership of this phoneme to all classed of the base of phonemes. The class of phoneme request is them the one which maximizes one degree of membership calculated according to reference vectors. For evaluation, a comparative study was operated to fix on the most perfect features extraction technique used.

Keywords

fuzzy logic; pattern classification; speech processing; vectors; MFCC; RASTA-PLP; fuzzy logic; fuzzy reference vectors; mel frequency cepstral coefficient; phonemes classification; relative spectral-perceptual linear prediction; speech analysis; Databases; Feature extraction; Fuzzy logic; Mel frequency cepstral coefficient; Speech; Support vector machine classification; Vectors; Features extraction; Fuzzy logic; Speech analysis; Speech recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Systems, Signals and Devices (SSD), 2011 8th International Multi-Conference on

Conference_Location

Sousse

Print_ISBN

978-1-4577-0413-0

Type

conf

DOI

10.1109/SSD.2011.5993568

Filename

5993568