{"_buckets": {"deposit": "833125b3-d31d-4ce1-aec5-266a52b74df4"}, "_deposit": {"id": "3893", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "3893"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/3893", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Audio Classification using Gaussian Mixture Model", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "This paper describes the work done on thedevelopment of an audio classification system. Audio recordingsare classified into basic audio types such as speech or music.Audio classification is processed in two parts, feature extractionand classification, which makes it suitable for differentapplications. In first part, input audio signal is transformed intofeature vectors, carrying characteristics information about thesignal. Audio Features for this task include Short Time Energy(SE), Zero Crossing Rate (ZC) and Mel Frequency CepstralCoefficient (MFCC). The second part classify feature vector intospeech or music. Gaussian Mixture Model (GMM) is used forclassification task. The overall accuracy rate of this paper getsaround 93%."}]}, "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": "2019-08-02"}], "displaytype": "preview", "download_preview_message": "", "file_order": 0, "filename": "Audio Classification using Gaussian Mixture Model.pdf", "filesize": [{"value": "11 Kb"}], "format": "application/pdf", "future_date_message": "", "is_thumbnail": false, "licensetype": "license_free", "mimetype": "application/pdf", "size": 11000.0, "url": {"url": "https://meral.edu.mm/record/3893/files/Audio Classification using Gaussian Mixture Model.pdf"}, "version_id": "cd41a933-bb65-4b30-be3a-f6ca4a411998"}]}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Third 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, Yuzana"}, {"subitem_authors_fullname": "Swe, Ei Mon Mon"}]}]}, "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": "2009-08-03"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/1615"}, "item_title": "Audio Classification using Gaussian Mixture Model", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000003893", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-08-02"}, "publish_date": "2019-08-02", "publish_status": "0", "recid": "3893", "relation": {}, "relation_version_is_last": true, "title": ["Audio Classification using Gaussian Mixture Model"], "weko_shared_id": -1}