{"created":"2020-09-01T14:03:26.626609+00:00","id":4075,"links":{},"metadata":{"_buckets":{"deposit":"7d6de357-a948-4cd1-a4d3-d22d6057159a"},"_deposit":{"id":"4075","owners":[],"pid":{"revision_id":0,"type":"recid","value":"4075"},"status":"published"},"_oai":{"id":"oai:meral.edu.mm:recid/4075","sets":["1582963302567:1597824273898"]},"communities":["ucsy"],"item_1583103067471":{"attribute_name":"Title","attribute_value_mlt":[{"subitem_1551255647225":"Speech Enhancement with Adaptive Wiener Filtering Approach","subitem_1551255648112":"en"}]},"item_1583103085720":{"attribute_name":"Description","attribute_value_mlt":[{"interim":"Presence of noise in speech signals deteriorates the performance of automatic speech recognition systems. Noise reduction is very important key-point of the speech enhancement in speech recognition system. The adaptive wiener filtering is a method used to enhance a speech signal which has been degraded by the noise. This approach is implemented in time domain and adaptation of the filter transfer function. The adaptive wiener filtering approach is improving the SNR in the enhanced speech signal. This approach emphasized to reduce the stationary noise. The spectrogram has been performed for speech signal corrupted by white noise, vehicle noise and babble noise. The results demonstrate that this method can perform better for white noise than the vehicle noise and babble noise."}]},"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":"2019-08-05"}],"displaytype":"preview","filename":"55182.pdf","filesize":[{"value":"716 Kb"}],"format":"application/pdf","licensetype":"license_note","mimetype":"application/pdf","url":{"url":"https://meral.edu.mm/record/4075/files/55182.pdf"},"version_id":"aa7d2ab9-41a4-4fc3-9da0-38cd5bd088c4"}]},"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":"Win, Ngu War Nyan"},{"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":"2009-12-30"},"item_1583159847033":{"attribute_name":"Identifier","attribute_value":"http://onlineresource.ucsy.edu.mm/handle/123456789/1780"},"item_title":"Speech Enhancement with Adaptive Wiener Filtering Approach","item_type_id":"21","owner":"1","path":["1597824273898"],"publish_date":"2019-08-05","publish_status":"0","recid":"4075","relation_version_is_last":true,"title":["Speech Enhancement with Adaptive Wiener Filtering Approach"],"weko_creator_id":"1","weko_shared_id":-1},"updated":"2021-12-13T01:21:35.441659+00:00"}