Evaluation of MFCC estimation techniques for music similarity

Spectral envelope parameters in the form of mel-frequency cepstral coefficients are often used for capturing timbral information of music signals in connection with genre classification applications. In this paper, we evaluate mel-frequency cepstral 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.