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Publicação
Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic Mask
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Orientador(es)
Resumo(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.
Descrição
Palavras-chave
Genetic Programming Multi pitch recognition Automatic piano music transcription Piano notes detection
Contexto Educativo
Citação
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.
Editora
IEEE