Hidden Markov Models (HMM) are compared to Gaussian Mixture Models
(GMM) for describing spectral similarity of songs. Contrary to previous
work we make a direct comparison based on the log-likelihood of songs
given an HMM or GMM. Whereas the direct comparison of log-likelihoods
clearly favors HMMs, this advantage in terms of modeling power does
not allow for any gain in genre classification accuracy.
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