Cartesian genetic programming applied to pitch estimation of piano notes

Created by W.Langdon from gp-bibliography.bib Revision:1.3872

@InProceedings{Inacio:2016:SSCI,
  author =       "Tiago Inacio and Rolando Miragaia and Gustavo Reis and 
                 Carlos Grilo and Francisco Fernandez",
  booktitle =    "2016 IEEE Symposium Series on Computational
                 Intelligence (SSCI)",
  title =        "Cartesian genetic programming applied to pitch
                 estimation of piano notes",
  year =         "2016",
  abstract =     "Pitch Estimation, also known as Fundamental Frequency
                 (F0) estimation, has been a popular research topic for
                 many years, and is still investigated nowadays. This
                 paper presents a novel approach to the problem of Pitch
                 Estimation, using Cartesian Genetic Programming (CGP).
                 We take advantage of evolutionary algorithms, in
                 particular CGP, to evolve mathematical functions that
                 act as classifiers. These classifiers are used to
                 identify piano notes' pitches in an audio signal. For a
                 first approach, the obtained results are very
                 promising: our error rate outperforms two of three
                 state-of-the-art pitch estimators.",
  keywords =     "genetic algorithms, genetic programming, cartesian
                 genetic programming",
  DOI =          "doi:10.1109/SSCI.2016.7850046",
  month =        dec,
  notes =        "Masters see http://hdl.handle.net/10400.8/2341
                 https://iconline.ipleiria.pt/handle/10400.8/2341

                 Also known as \cite{7850046}",
}

Genetic Programming entries for Tiago Joao Leite Inacio Rolando Miragaia Gustavo Miguel Jorge dos Reis Carlos Grilo Francisco Fernandez de Vega

Citations