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Evolving a multi-classifier system with cartesian genetic programming for multi-pitch estimation of polyphonic piano music

Published:22 April 2021Publication History

ABSTRACT

This paper presents a new method for multi-pitch estimation on piano recordings. We propose a framework based on a set of classifiers to analyze the audio input and identify the piano notes present on the given audio signal. Our system's classifiers were evolved using Cartesian Genetic Programming: we take advantage of Cartesian Genetic Programming to evolve a set of mathematical functions that act as independent classifiers for piano notes. Our latest improvements are also presented, including test results using F-measure metrics. Our system architecture is also described to show the feasibility of its parallelization and implementation as a real time system. The proposed approach achieved competitive results, when compared to the state of the art.

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            cover image ACM Conferences
            SAC '21: Proceedings of the 36th Annual ACM Symposium on Applied Computing
            March 2021
            2075 pages
            ISBN:9781450381048
            DOI:10.1145/3412841

            Copyright © 2021 ACM

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            • Published: 22 April 2021

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