Conference paper
Evaluation of mfcc estimation techniques for music similarity
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.
Language: | English |
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Publisher: | IEEE |
Year: | 2006 |
Pages: | 1-5 |
Proceedings: | 14th European Signal Processing Conference |
ISSN: | 22195491 |
Types: | Conference paper |
Abstracts Gaussian Mixture models Gaussian processes MFCC estimation techniques MVDR spectral estimator Mel-frequency cepstral coefficients audio signal processing genre classification genre classification applications music music signals music similarity probabilistic classifier signal independent linear prediction simpler FFT spectral envelope parameters timbral information