Paper Info
Title
A Modified Mfcc Feature Extraction Technique For Robust Speaker Recognition
Abstract
In Speaker Recognition (SR) system, feature extraction is one of the crucial steps where the particular speaker related information are extracted. The state of the art algorithm for this purpose is Mel Frequency Cepstral Coefficient (MFCC), and its complementary feature, Inverted Mel Frequency Cepstral Coefficient (IMFCC). MFCC is based on mel scale and IMFCC is based on inverted mel (imel) scale. In this paper, another complementary set of features are proposed which is also based on mel-imel scale, and the filtering operation makes these set of features different from MFCC and IMFCC. On the background of this proposed features, the filter banks are placed linearly on the nonlinear scale which makes the features different from the state-of-theart feature extraction techniques. We call these two features as mMFCC, and mIMFCC. mMFCC is based on mel scale, whereas, mIMFCC is based on imel. mMFCC is compared with MFCC and mIMFCC is compared with IMFCC. The result has been verified on two standard databases YOHO, and POLYCOST using Gaussian Mixture Model (GMM) as the speaker modeling paradigm.
Year
Venue
Keywords
2015
2015 INTERNATIONAL CONFERENCE ON ADVANCES IN COMPUTING, COMMUNICATIONS AND INFORMATICS (ICACCI)
MFCC, IMFCC, mMFCC, mIMFCC, Feature extraction, Fusion, Triangular filter, GMM
Field
DocType
Citations 
Mel-frequency cepstrum,Pattern recognition,Computer science,Filter (signal processing),Mel scale,Feature extraction,Speech recognition,Speaker recognition,Artificial intelligence,Mixture model
Conference
0
PageRank 
References 
Authors
0.34
6
2
Name
Order
Citations
PageRank
Diksha Sharma100.34
Israj Ali201.01