Cartesian genetic programming applied to pitch estimation of piano notes

Created by W.Langdon from gp-bibliography.bib Revision:1.8592

@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