Feature extraction and classification techniques for speaker recognition: A review

Author

Dhameliya, Kinnal ; Bhatt, Ninad

Author_Institution

Electronics and Communication Department, C.G Patel Institute of Technology, Bardoli, Surat, India

fYear

2015

fDate

24-25 Jan. 2015

Firstpage

1

Lastpage

4

Abstract

In recent scenario speaker recognition is used in many places for security purpose. Speaker recognition is technique which can verify or identify the person who is speaking. It is different than speech recognition system. In this paper we have discussed the feature extraction techniques like Mel Frequency Cepstral Co-efficient (MFCC), Linear Predictive Coding (LPC) etc. and classification techniques like Gaussian Mixture Model (GMM), Artificial Neural Networks (ANN) etc. that is available for speaker recognition. Also the survey is about how to get better efficiency in terms of speaker recognition rate by simply modifying the existing feature extraction and classification techniques.

Keywords

Artificial neural networks; Feature extraction; Mel frequency cepstral coefficient; Speaker recognition; Speech; Speech recognition; Artificial Neural Network (ANN); Gaussian Mixture Model (GMM); Linear Predictive Coding (LPC); Mel frequency Cepstral Co-efficient (MFCC); Speaker Recognition;

fLanguage

English

Publisher

ieee

Conference_Titel

Electrical, Electronics, Signals, Communication and Optimization (EESCO), 2015 International Conference on

Conference_Location

Visakhapatnam, India

Print_ISBN

978-1-4799-7676-8

Type

conf

DOI

10.1109/EESCO.2015.7253831

Filename

7253831