Evaluating Text Features for Lyrics-Based Songwriter Prediction

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dc.contributor.authorKirmaci, Basar
dc.contributor.authorOgul, Hasan
dc.contributor.pubmedID978-1-4673-7939-7en_US
dc.date.accessioned2023-11-20T12:36:46Z
dc.date.available2023-11-20T12:36:46Z
dc.date.issued2015
dc.description.abstractWe offer an automated way of estimating the author of a song using only its lyrics content. To this end, we introduce a complete text classification framework which takes raw lyrics data as input and report estimated songwriter. The performance of the system is evaluated based on its classification and retrieval ability on a large dataset of Turkish songs, which was collected in this study. The results promote the use of such technique as a complementary tool in music information retrieval applications.en_US
dc.identifier.endpage409en_US
dc.identifier.issn1562-5850en_US
dc.identifier.scopus2-s2.0-84963690245en_US
dc.identifier.startpage405en_US
dc.identifier.urihttp://hdl.handle.net/11727/10882
dc.identifier.wos000377211000066en_US
dc.language.isoengen_US
dc.relation.journal19th IEEE International Conference on Intelligent Engineering Systems (INES)en_US
dc.rightsinfo:eu-repo/semantics/closedAccessen_US
dc.subjectMusic information retrievalen_US
dc.subjecttext classificationen_US
dc.subjectauthorship attributionen_US
dc.titleEvaluating Text Features for Lyrics-Based Songwriter Predictionen_US
dc.typeconferenceObjecten_US

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