Publication
Cartesian genetic programming applied to pitch estimation of piano notes
dc.contributor.author | Inacio, Tiago | |
dc.contributor.author | Miragaia, Rolando | |
dc.contributor.author | Reis, Gustavo | |
dc.contributor.author | Grilo, Carlos | |
dc.contributor.author | Fernandez, Francisco | |
dc.date.accessioned | 2025-10-15T13:33:02Z | |
dc.date.available | 2025-10-15T13:33:02Z | |
dc.date.issued | 2016-12 | |
dc.description.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. | eng |
dc.identifier.citation | T. Inácio, R. Miragaia, G. Reis, C. Grilo and F. Fernandéz, "Cartesian genetic programming applied to pitch estimation of piano notes," 2016 IEEE Symposium Series on Computational Intelligence (SSCI), Athens, Greece, 2016, pp. 1-7, doi: 10.1109/SSCI.2016.7850046 | |
dc.identifier.doi | 10.1109/ssci.2016.7850046 | |
dc.identifier.uri | http://hdl.handle.net/10400.8/14269 | |
dc.language.iso | eng | |
dc.peerreviewed | yes | |
dc.publisher | IEEE | |
dc.relation.hasversion | https://ieeexplore.ieee.org/document/7850046 | |
dc.relation.ispartof | 2016 IEEE Symposium Series on Computational Intelligence (SSCI) | |
dc.rights.uri | N/A | |
dc.title | Cartesian genetic programming applied to pitch estimation of piano notes | eng |
dc.type | conference paper | |
dspace.entity.type | Publication | |
oaire.citation.conferenceDate | 2016-12-06 | |
oaire.citation.conferencePlace | Athens, Greece | |
oaire.citation.title | 2016 IEEE Symposium Series on Computational Intelligence (SSCI) | |
oaire.version | http://purl.org/coar/version/c_970fb48d4fbd8a85 | |
person.familyName | Miragaia | |
person.familyName | Jorge dos Reis | |
person.familyName | Grilo | |
person.givenName | Rolando | |
person.givenName | Gustavo Miguel | |
person.givenName | Carlos | |
person.identifier.ciencia-id | C712-E02E-0ED2 | |
person.identifier.ciencia-id | C41A-BC63-08E6 | |
person.identifier.ciencia-id | 081D-025A-33BC | |
person.identifier.orcid | 0000-0003-4213-9302 | |
person.identifier.orcid | 0000-0002-5903-8754 | |
person.identifier.orcid | 0000-0001-9727-905X | |
person.identifier.rid | GLS-3615-2022 | |
person.identifier.rid | M-9551-2013 | |
person.identifier.scopus-author-id | 26422369700 | |
person.identifier.scopus-author-id | 23466972200 | |
relation.isAuthorOfPublication | c3934650-8cbe-40cd-bb29-31c57baa49e2 | |
relation.isAuthorOfPublication | 77b7fb9b-3584-4057-a3d8-de29d3fab6c1 | |
relation.isAuthorOfPublication | f2075503-40b3-49da-81c3-e0c50f97c9ab | |
relation.isAuthorOfPublication.latestForDiscovery | c3934650-8cbe-40cd-bb29-31c57baa49e2 |
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