Abstract
Automatic recognition of multiple musical instruments in polyphonic and polytimbral music is a difficult task, but often attempted to perform by MIR researchers recently. In papers published so far, the proposed systems were validated mainly on audio data obtained through mixing of isolated sounds of musical instruments. This paper tests recognition of instruments in real recordings, using a recognition system which has multilabel and hierarchical structure. Random forest classifiers were applied to build the system. Evaluation of our model was performed on audio recordings of classical music. The obtained results are shown and discussed in the paper.
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Kubera, E., Wieczorkowska, A., Raś, Z., Skrzypiec, M. (2010). Recognition of Instrument Timbres in Real Polytimbral Audio Recordings. In: Balcázar, J.L., Bonchi, F., Gionis, A., Sebag, M. (eds) Machine Learning and Knowledge Discovery in Databases. ECML PKDD 2010. Lecture Notes in Computer Science(), vol 6322. Springer, Berlin, Heidelberg. https://doi.org/10.1007/978-3-642-15883-4_7
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