Abstract
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.
| Original language | English |
|---|---|
| Title of host publication | Proceedings of the 8th International Conference on Digital Audio Effects (DAFx 2005), Madrid, Spain |
| Number of pages | 6 |
| Publication status | Published - 2005 |
Fields of science
- 102 Computer Sciences
- 102001 Artificial intelligence
- 102003 Image processing
- 102015 Information systems
- 202002 Audiovisual media