Repository logo
 
Publication

Evolutionary algorithms and automatic transcription of music

2012-07-07Conference paper Restricted access
Simple item page
datacite.subject.fosCiências Naturais::Matemáticas
datacite.subject.fosEngenharia e Tecnologia::Outras Engenharias e Tecnologias
datacite.subject.sdg08:Trabalho Digno e Crescimento Económico
datacite.subject.sdg09:Indústria, Inovação e Infraestruturas
datacite.subject.sdg10:Reduzir as Desigualdades
dc.contributor.authorReis, Gustavo
dc.contributor.authorFernandéz, Francisco
dc.contributor.authorFerreira, Aníbal
dc.date.accessioned2026-01-15T13:32:11Z
dc.date.available2026-01-15T13:32:11Z
dc.date.issued2012-07-07
dc.description.abstractThe main problem behind Automatic Transcription (Multiple Fundamental Frequency - F0 - Estimation) relies on its complexity. Harmonic collision and partial overlapping create a frequency lattice that is almost impossible to deconstruct. Although traditional approaches to this problem of rely mainly in Digital Signal Processing (DSP) techniques, evolutionary algorithms have been applied recently to this problem and achieved competitive results. We describe all evolutionary approaches to the problem of automatic music transcription and how some were improved so they could achieve competitive results. Finally, we show how the best evolutionary approach performs on piano transcription, when compared with the state-of-the-art.eng
dc.description.sponsorshipThe authors acknowledge the support of Spanish Ministry of Science and Innovation under project ANYSELF (TIN2011-28627-C04), Gobierno de Extremadura, under projects GRU09105, GR10029 and Municipality of Almendralejo.
dc.identifier.citationGustavo Reis, Francisco Fernandéz, and Aníbal Ferreira. 2012. Evolutionary algorithms and automatic transcription of music. In Proceedings of the 14th annual conference companion on Genetic and evolutionary computation (GECCO '12). Association for Computing Machinery, New York, NY, USA, 477–484. https://doi.org/10.1145/2330784.2330857
dc.identifier.doi10.1145/2330784.2330857
dc.identifier.isbn978-145031178-6
dc.identifier.urihttp://hdl.handle.net/10400.8/15343
dc.language.isoeng
dc.peerreviewedyes
dc.publisherAssociation for Computing Machinery (ACM)
dc.relation.hasversionhttps://dl.acm.org/doi/10.1145/2330784.2330857
dc.relation.ispartofProceedings of the 14th annual conference companion on Genetic and evolutionary computation
dc.rights.uriN/A
dc.subjectAutomatic Music Transcription
dc.subjectPitch Estimation
dc.subjectMultiple F0 Estimation
dc.subjectGenetic Algorithms
dc.titleEvolutionary algorithms and automatic transcription of music
dc.typeconference paper
dspace.entity.typePublication
oaire.citation.conferenceDate2012
oaire.citation.endPage484
oaire.citation.startPage477
oaire.citation.titleProceedings of the 14th annual conference companion on Genetic and evolutionary computation (GECCO '12)
oaire.versionhttp://purl.org/coar/version/c_970fb48d4fbd8a85
person.familyNameJorge dos Reis
person.givenNameGustavo Miguel
person.identifier.ciencia-idC41A-BC63-08E6
person.identifier.orcid0000-0002-5903-8754
relation.isAuthorOfPublication77b7fb9b-3584-4057-a3d8-de29d3fab6c1
relation.isAuthorOfPublication.latestForDiscovery77b7fb9b-3584-4057-a3d8-de29d3fab6c1

Files

Original bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
2330784.2330857.pdf
Size:
817.62 KB
Format:
Adobe Portable Document Format
Download
License bundle
Now showing 1 - 1 of 1
No Thumbnail Available
Name:
license.txt
Size:
1.32 KB
Format:
Item-specific license agreed upon to submission
Description:
Download

Collections

ESTG - Comunicações em conferências e congressos internacionais