{"_buckets": {"deposit": "26fc523e-314e-4030-bcb8-0f50b7cb98f6"}, "_deposit": {"id": "4929", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4929"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4929", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Classification of Music Emotion with Gaussian Mixture Model (GMM)", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "Music is a link between cognition and emotion, andpeople are not able to share same feeling for a song.There has a need to process vast qualities of musicaldata. One of the operations is music emotionclassification which is very popular today and anautomatic extraction is needed, relating to variousaspects of music. Music emotion recognition througha learning model is considered in this paper. Inorder to capture the salient nature of music signalsfeatures such as cepstral is applied. Classification ofmusic signals is considered by Gaussian MixtureModel (GMM). In this approach, Thayer’s model isadopted for the description of emotions. This musicmood detection approach is validated through anexperimental study on a dataset containing 60famous popular songs from English albums."}]}, "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": "2019-07-12"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "psc2010paper (118).pdf", "filesize": [{"value": "108 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 108000.0, "url": {"url": "https://meral.edu.mm/record/4929/files/psc2010paper (118).pdf"}, "version_id": "7f5cd4c5-42cb-4dec-b501-0205767cae74"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Fifth 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": "Ko, Myat Ko"}]}]}, "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": "2010-12-16"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/830"}, "item_title": "Classification of Music Emotion with Gaussian Mixture Model (GMM)", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004929", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-12"}, "publish_date": "2019-07-12", "publish_status": "0", "recid": "4929", "relation": {}, "relation_version_is_last": true, "title": ["Classification of Music Emotion with Gaussian Mixture Model (GMM)"], "weko_shared_id": -1}