Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic Mask

Miragaia, Rolando; Reis, Gustavo; Fernandéz de Vega, Francisco; Chávez, Francisco

http://hdl.handle.net/10400.8/6283

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Authors

Miragaia, Rolando

Reis, Gustavo

Fernandéz de Vega, Francisco

Chávez, Francisco

Abstract(s)

Piano notes recognition, or pitch estimation of piano notes has been a popular research topic for many years, and is still investigated nowadays. It is a fundamental task during the process of automatic music transcription (extracting the musical score from an acoustic signal). We take advantage of Cartesian Genetic Programming (CGP) to evolve mathematical functions that act as independent classifiers for piano notes. These classifiers are then used to identify the presence of piano notes in polyphonic audio signals. This paper describes our technique and the latest improvements made in our research. The main feature is the introduction of spectral harmonic masks in the binarization process for measuring the fitness values that has allowed to improve the classification rate: 10% in the F-measure mean result. Our system architecture is also described to show the feasibility of its parallelization, which will reduce the computing time.

Keywords

Genetic Programming Multi pitch recognition Automatic piano music transcription Piano notes detection

URI

http://hdl.handle.net/10400.8/6283

Citation

R. Miragaia, G. Reis, F. F. de Vega and F. Chávez, "Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic Mask," 2020 IEEE Symposium Series on Computational Intelligence (SSCI), 2020, pp. 1800-1807, doi: 10.1109/SSCI47803.2020.9308178.