{"created":"2020-09-01T14:22:04.472468+00:00","id":4225,"links":{},"metadata":{"_buckets":{"deposit":"7ce89022-8e2e-41b1-98f7-40876898eb51"},"_deposit":{"id":"4225","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4225"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4225","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"A Framework for Multi-Label Music Mood Classification","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Music is the effective communication mediumamong people. Studying music mood can help inmusic understanding, music retrieval, and someother music-related applications. This paperpresents a hierarchical framework with a new moodtaxonomy model to automate the task of moodclassification from acoustic music data based onwestern music psychology theory. This systemproposes hierarchical framework with new moodtaxonomy model. The proposed mood taxonomymodel is combined by the Thayer’s 2 Dimensionmodel and Schubert’s updated Hevner adjectivechecklist. The 60 famous English songs are used asthe standard database in this system which is createdby literature. The verse and chorus part from thewhole song is extracted manually for processing inthis proposed system. The extracted music clip issegmented by image region growing method toseparate homogenous part on the entire music clip.Then, the feature sets from the separated musictrimmed are extracted to inject the Fuzzy SupportVector Machine (SFVM). To solve the multi-labelclassification problem, one-against-one (O-A-O)multi class classification method are used. Thehierarchical framework with new mood taxonomymodel has the advantage of reducing the number ofclassifier used for O-A-O approach."}]},"item_1583103108160":{"attribute_name":"Keywords","attribute_value":[]},"item_1583103120197":{"attribute_name":"Files","attribute_type":"file","attribute_value_mlt":[{"accessrole":"open_access","date":[{"dateType":"Available","dateValue":"2019-08-06"}],"displaytype":"preview","filename":"59026.pdf","filesize":[{"value":"105 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4225/files/59026.pdf"},"version_id":"abb38ea5-d178-4ff6-b100-26573ee9ebf9"}]},"item_1583103131163":{"attribute_name":"Journal articles","attribute_value_mlt":[{"subitem_issue":"","subitem_journal_title":"Fourth Local Conference on Parallel and Soft Computing","subitem_pages":"","subitem_volume":""}]},"item_1583103147082":{"attribute_name":"Conference papers","attribute_value_mlt":[{"subitem_acronym":"","subitem_c_date":"","subitem_conference_title":"","subitem_part":"","subitem_place":"","subitem_session":"","subitem_website":""}]},"item_1583103211336":{"attribute_name":"Books/reports/chapters","attribute_value_mlt":[{"subitem_book_title":"","subitem_isbn":"","subitem_pages":"","subitem_place":"","subitem_publisher":""}]},"item_1583103233624":{"attribute_name":"Thesis/dissertations","attribute_value_mlt":[{"subitem_awarding_university":"","subitem_supervisor(s)":[{"subitem_supervisor":""}]}]},"item_1583105942107":{"attribute_name":"Authors","attribute_value_mlt":[{"subitem_authors":[{"subitem_authors_fullname":"Myint, Ei Ei Pe"}]}]},"item_1583108359239":{"attribute_name":"Upload type","attribute_value_mlt":[{"interim":"Publication"}]},"item_1583108428133":{"attribute_name":"Publication type","attribute_value_mlt":[{"interim":"Article"}]},"item_1583159729339":{"attribute_name":"Publication date","attribute_value":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1917"},"item_title":"A Framework for Multi-Label Music Mood Classification","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-08-06","publish_status":"0","recid":"4225","relation_version_is_last":true,"title":["A Framework for Multi-Label Music Mood Classification"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T04:01:14.993429+00:00"}