Text dependent speaker recognition using discrete stationary wavelet transform and PCA

Author

Jayakumar, Akshay ; Vimal Krishnan, V.R. ; Babu Anto, P.

Author_Institution

Sch. of Inf. Sci. & Technol., Kannur Univ., Kannur, India

fYear

2009

Firstpage

1

Lastpage

4

Abstract

In this paper we present an effective and robust method for speaker identification based on discrete stationary wavelet transform and principal component analysis techniques. The time invariant characteristic of SWT is particularly used in this paper for Speaker recognition. We have selected PCA as it is a core of modern data analysis. For classification purpose we have used Artificial Neural Network. One hundred and fifty samples are collected from 10 different people at various time intervals for the initial study. Data base is created from a spoken language Malayalam.

Keywords

discrete wavelet transforms; neural nets; principal component analysis; speaker recognition; text analysis; Malayalam language; artificial neural network; data analysis; discrete stationary wavelet transform; principal component analysis; text dependent speaker recognition; Application software; Artificial neural networks; Data analysis; Data mining; Discrete wavelet transforms; Feature extraction; Neurons; Principal component analysis; Speaker recognition; Wavelet analysis; DSWT; PCA; Speaker recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Current Trends in Information Technology (CTIT), 2009 International Conference on the

Conference_Location

Dubai

Print_ISBN

978-1-4244-5754-0

Electronic_ISBN

978-1-4244-5756-4

Type

conf

DOI

10.1109/CTIT.2009.5423125

Filename

5423125