Music Information Retrieval – Soft Computing Versus Statistics
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Publisher
Springer International Publishing
Link
http://link.springer.com/content/pdf/10.1007/978-3-319-24369-6_3
Reference42 articles.
1. Aucouturier, J.-J., Pachet, F.: Representing musical genre: A state of art. J. New Music Research 32(1), 83–93 (2003)
2. Bergstra, J., Casagrande, N., Erhan, D., Eck, D., Kegl, B.: Aggregate features and AdaBoost for music classification. Machine Learning 65(2–3), 473–484 (2006)
3. Eweret, S., Prado, B., Muller, M., Plumbley, M.: Score-Informed Source Separation for Musical Audio Recordings. Signal Processing Magazine, 116–124 (2014)
4. Ekstrand, M.D., Riedl, J.T., Konstan, J.A.: Collaborative Filtering Recommender Systems. Foundations and Trends in Human-Computer Interaction 4(2), 81–173 (2011). doi: 10.1561/1100000009
5. Ghias, A., Logan, J., Chamberlin, D., Smith, B.C.: Query by humming - musical information retrieval in an audio database. In: ACM Multimedia 1995, San Francisco (1995)
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