{"_buckets": {"deposit": "b29acf5a-7f24-48fb-ba18-8e07237910fe"}, "_deposit": {"id": "3481", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3481"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3481", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Depression Detection from Speech Emotion Recognition", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "The recognition of the internal emotional stateof a person plays an important role in several humanrelatedfields. Emotions constitute an essential part ofour existence as it exerts great influence on thephysical and mental health of people. Depression is acommon mental disorder. Developments in affectivesensing technology with focus on acoustic features willpotentially bring a change due to depressed patients’slow, hesitating, monotonous voice as remarkablecharacteristics. This paper will present classificationof emotions and from it, depression is detected byusing speech signals. Both time and frequency domainfeatures will be used in feature vector extraction. Infeature extraction, the paper will use wavelettransform and MFCC. DenseNet will be used to detectthe emotion, classify the type of emotion and thendepression."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "internal emotional state"}, {"interim": "feature vector extraction"}, {"interim": "wavelet transform"}, {"interim": "MFCC"}, {"interim": "Densenet"}, {"interim": "Depression"}]}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value_mlt": [{"accessrole": "open_access", "date": [{"dateType": "Available", "dateValue": "2019-07-23"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "ICCA 2019 Proceedings Book-pages-312-316.pdf", "filesize": [{"value": "799 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 799000.0, "url": {"url": "https://meral.edu.mm/record/3481/files/ICCA 2019 Proceedings Book-pages-312-316.pdf"}, "version_id": "fec17b15-7dbe-4ef0-a61b-1699d4fa059e"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Seventeenth International Conference on Computer Applications(ICCA 2019)", "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": "Mar, Lwin Lwin"}, {"subitem_authors_fullname": "Pa, Win Pa"}]}]}, "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": "2019-02-27"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1227"}, "item_title": "Depression Detection from Speech Emotion Recognition", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003481", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-23"}, "publish_date": "2019-07-23", "publish_status": "0", "recid": "3481", "relation": {}, "relation_version_is_last": true, "title": ["Depression Detection from Speech Emotion Recognition"], "weko_shared_id": -1}