Estimation of musical sound separation algorithm effectiveness employing neural networks
Journal of Intelligent Information Systems - Special issue: Intelligent multimedia applications
Cooperative music retrieval based on automatic indexing of music by instruments and their types
Cooperative music retrieval based on automatic indexing of music by instruments and their types
Musical Instruments in Random Forest
ISMIS '09 Proceedings of the 18th International Symposium on Foundations of Intelligent Systems
Journal of Intelligent Information Systems
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In this paper, the influence of the selected sound features on distinguishing between musical instruments is presented. The features were chosen basing on our previous research. Coherent groups of features were created on the basis of significant features, adding complementary ones according to the parameterization method applied, to constitute small, homogenous groups. Next, we investigate (for each feature group separately) if there exist significant differences between means of these features for the studied instruments. We apply multivariate analysis of variance along with post hoc analysis in the form of homogeneous groups, defined by mean values of the investigated features for our instruments. If a statistically significant difference is found, then the homogenous group is established. Such a group may consist of one instrument (distinguished by this feature), or more (instruments similar wrt. this feature). The results show which instruments can be best discerned by which features.