Computational Models of Similarity for Drum Samples

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

• Type: Journal
• Year: 2008
• Where: TASLP
• Authors: Elias Pampalk, Perfecto Herrera, Masataka Goto
• Keywords: Evaluate, Instrument Class, Similarity Models, TASLP 2008