Machine Learning
Rough Sets as A Tool for Audio Signal Classification
ISMIS '99 Proceedings of the 11th International Symposium on Foundations of Intelligent Systems
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
Recognition of instrument timbres in real polytimbral audio recordings
ECML PKDD'10 Proceedings of the 2010 European conference on Machine learning and knowledge discovery in databases: Part II
All that jazz in the random forest
ISMIS'11 Proceedings of the 19th international conference on Foundations of intelligent systems
Playing in unison in the random forest
SIIS'11 Proceedings of the 2011 international conference on Security and Intelligent Information Systems
Analysis of Recognition of a Musical Instrument in Sound Mixes Using Support Vector Machines
Fundamenta Informaticae
A comparison of random forests and ferns on recognition of instruments in jazz recordings
ISMIS'12 Proceedings of the 20th international conference on Foundations of Intelligent Systems
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In this paper we investigate the problem of recognizing the full set of instruments playing in a sound mix. Random mixes of 2-5 instruments (out of 14) were created and parameterized to obtain experimental data. Sound samples were taken from 3 audio data sets. For classification purposes, we used a battery of one-instrument sensitive random forest classifiers, and obtained quite good results.