Multi Pitch Estimation of Piano Music using Cartesian Genetic Programming with Spectral Harmonic Mask
Created by W.Langdon from
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- @InProceedings{Miragaia:2020:SSCI,
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author = "Rolando Miragaia and Gustavo Reis and
Francisco Fernandez {de Vega} and Francisco Chavez",
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title = "Multi Pitch Estimation of Piano Music using Cartesian
Genetic Programming with Spectral Harmonic Mask",
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booktitle = "2020 IEEE Symposium Series on Computational
Intelligence (SSCI)",
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year = "2020",
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pages = "1800--1807",
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month = dec,
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keywords = "genetic algorithms, genetic programming, cartesian
genetic programming",
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DOI = "doi:10.1109/SSCI47803.2020.9308178",
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abstract = "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:
1percent 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.",
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notes = "Also known as \cite{9308178}",
- }
Genetic Programming entries for
Rolando Miragaia
Gustavo Miguel Jorge dos Reis
Francisco Fernandez de Vega
Francisco Chavez de la O
Citations