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Improving instrument recognition in polyphonic music through system integration

Giannoulis, D., Benetos, E., Klapuri, A. & Plumbley, M. D. (2014). Improving instrument recognition in polyphonic music through system integration. Paper presented at the 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), 04-05-2014 - 09-05-2014, Florence, Italy. doi: 10.1109/ICASSP.2014.6854599


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.

Publication Type: Conference or Workshop Item (Paper)
Additional Information: © 2014 IEEE. Personal use of this material is permitted. Permission from IEEE must be obtained for all other uses, in any current or future media, including reprinting/republishing this material for advertising or promotional purposes, creating new collective works, for resale or redistribution to servers or lists, or reuse of any copyrighted component of this work in other works.
Publisher Keywords: Musical instrument recognition, automatic music transcription, music signal analysis
Subjects: M Music and Books on Music
Q Science > QA Mathematics > QA75 Electronic computers. Computer science
Departments: School of Science & Technology > Computer Science
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