{"_buckets": {"deposit": "ffc2f820-f535-4dba-8ec7-0435fe86757d"}, "_deposit": {"id": "4685", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4685"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4685", "sets": ["user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Syllable-based Myanmar-English Neural Machine Translation", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "The paper presents the first large scaleevaluation of the quality of Syllable-based NeuralMachine Translation (Syllable-NMT) system forMyanmar-English pair. Neural Machine Translation(NMT) system has reached state-of-the-arts resultson some languages. However, one of the mainchallenges that NMT still faces is dealing with verylarge vocabularies and morphologically richlanguages. Like other low-resources languages,Myanmar Language has a lots of morphologyinformation. This issue lead is to increase theambiguity and to decrease the quality of translationresults. Moreover, rule-based and phrase-basedtechniques were used in the existing research onMyanmar translation with the small amount ofparallel corpus. Therefore, a large amount ofparallel corpus is prepared and introduces a NMTmodel that maps a source syllable sequence to atarget word sequences to address the morphologicalproblems. In addition, this paper shows someexperiments results and compare them. Our resultsshow that syllable-NMT system is able to surpassthan the character-based and word-based NMTsystems by 5 BLEU."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value": []}, "item_1583103120197": {"attribute_name": "Files", "attribute_type": "file", "attribute_value": []}, "item_1583103131163": {"attribute_name": "Journal articles", "attribute_value_mlt": [{"subitem_issue": "", "subitem_journal_title": "Sixteenth International Conferences on Computer Applications(ICCA 2018)", "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": "Sin, Yi Mon Shwe"}, {"subitem_authors_fullname": "Soe, Khin Mar"}]}]}, "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": "2018-02-22"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/350"}, "item_title": "Syllable-based Myanmar-English Neural Machine Translation", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004685", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-03"}, "publish_date": "2019-07-03", "publish_status": "0", "recid": "4685", "relation": {}, "relation_version_is_last": true, "title": ["Syllable-based Myanmar-English Neural Machine Translation"], "weko_shared_id": -1}