@CONFERENCE\{IMM2006-04413,
    author       = "J. H. Jensen and M. G. Christensen and M. Murthi and S. H. Jensen",
    title        = "Evaluation of mfcc estimation techniques for music similarity",
    year         = "2006",
    booktitle    = "European Signal Processing Conference, {EUSIPCO}",
    volume       = "",
    series       = "",
    editor       = "",
    publisher    = "",
    organization = "",
    address      = "",
    url          = "http://www2.compute.dtu.dk/pubdb/pubs/4413-full.html",
    abstract     = "Spectral envelope parameters in the form of mel-frequencycepstral coefficients are often used for capturing timbral information of music signals in connection with genre classification applications. In this paper, we evaluate mel-frequencycepstral coefficient (MFCC) estimation techniques, namely the classical {FFT} and linear prediction based implementations and an implementation based on the more recent {MVDR} spectral estimator. The performance of these methods are evaluated in genre classification using a probabilistic classifier based on Gaussian Mixture models. MFCCs based on fixed order, signal independent linear prediction and {MVDR} spectral estimators did not exhibit any statistically significant improvement over MFCCs based on the simpler {FFT}."
}