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Analysis of MFCC and Multitaper MFCC Feature Extraction Methods
| International Journal of Computer Applications |
| Foundation of Computer Science (FCS), NY, USA |
| Volume 131 - Number 4 |
| Year of Publication: 2015 |
| Authors: Rupali G. Shintri, S.K. Bhatia |
10.5120/ijca2015906883
|
Rupali G. Shintri, S.K. Bhatia . Analysis of MFCC and Multitaper MFCC Feature Extraction Methods. International Journal of Computer Applications. 131, 4 ( December 2015), 7-10. DOI=10.5120/ijca2015906883
Abstract
In speech & audio applications, short-term signal spectrum is often represented using mel-freuency cepstral coefficient (MFCC) computed from a windowed discrete Fourier transform (DFT). Windowing reduces spectral leakage but variance of the spectrum estimate remains high. An extension to windowed DFT is called multitaper method which uses multiple time domain windows which are called as tapers with frequency domain averaging. Then detailed statistical analysis of MFCC bias & variance is done. For speaker verification the extracted feature is used to design a model using classifier (GMM), which implements likelihood ratio test to decide whether to accept or deny the registered speaker.
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