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Computational Models of Similarity for Drum Samples

Title Computational Models of Similarity for Drum Samples
Publication Type Journal Article
Year of Publication 2008
Authors Pampalk, E. , Herrera P. , & Goto M.
Journal Title IEEE Transactions on Audio, Speech, and Language Processing
Volume 16
Issue 2
Pages 408-423
Journal Date 02/2008
Abstract In this paper, we optimize and evaluate computational models of similarity for sounds from the same instrument class. We investigate four instrument classes: bass drums, snare drums, high-pitched toms, and low-pitched toms. We evaluate two similarity models: one is defined in the ISO/IEC MPEG-7 standard, and the other is based on auditory images. For the second model, we study the impact of various parameters. We use data from listening tests, and instrument class labels to evaluate the models. Our results show that the model based on auditory images yields a very high average correlation with human similarity ratings and clearly outperforms the MPEG-7 recommendation. The average correlations range from 0.89¿0.96 depending on the instrument class. Furthermore, our results indicate that instrument class data can be used as alternative to data from listening tests to evaluate sound similarity models.
preprint/postprint document files/publications/Pampalk-Herrera-Goto-IEEETASLP-2008.pdf