Improving instrument recognition in polyphonic music through system integration

Abstract

A method is proposed for instrument recognition in polyphonic music which combines two independent detector systems. A polyphonic musical instrument recognition system using a missing feature approach and an automatic music transcription system based on shift invariant probabilistic latent component analysis that includes instrument assignment. We propose a method to integrate the two systems by fusing the instrument contributions estimated by the first system onto the transcription system in the form of Dirichlet priors. Both systems, as well as the integrated system are evaluated using a dataset of continuous polyphonic music recordings. Detailed results that highlight a clear improvement in the performance of the integrated system are reported for different training conditions.

DOI: 10.1109/ICASSP.2014.6854599

Extracted Key Phrases

5 Figures and Tables

Cite this paper

@article{Giannoulis2014ImprovingIR, title={Improving instrument recognition in polyphonic music through system integration}, author={Dimitrios Giannoulis and Emmanouil Benetos and Anssi Klapuri and Mark D. Plumbley}, journal={2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)}, year={2014}, pages={5222-5226} }