MERAL Myanmar Education Research and Learning Portal
Item
{"_buckets": {"deposit": "43552e1f-8f86-43a0-afa9-ea9f4e91db8b"}, "_deposit": {"id": "4671", "owners": [], "pid": {"revision_id": 0, "type": "recid", "value": "4671"}, "status": "published"}, "_oai": {"id": "oai:meral.edu.mm:recid/4671", "sets": ["1597824273898", "user-ucsy"]}, "communities": ["ucsy"], "item_1583103067471": {"attribute_name": "Title", "attribute_value_mlt": [{"subitem_1551255647225": "Automatic Speech Recognition on Spontaneous Interview Speech", "subitem_1551255648112": "en"}]}, "item_1583103085720": {"attribute_name": "Description", "attribute_value_mlt": [{"interim": "This paper presents a spontaneous speechrecognition system for Myanmar language. Automaticspeech recognition (ASR) on some controlled speechhas achieved almost human performance. However, theperformance of spontaneous speech is drasticallydecreased due to the diversity of speaking styles, speakrate, presence of additive and non-linear distortion,accents and weakened articulation. In this study, webuilt a recognizer for Myanmar Interview speech byusing the classical Gaussian Mixture Model basedHidden Markov Model (HMM-GMM) approach. Weinvested that the effect of variation on acoustic featureand number of senones and Gaussian densities onMyanmar Interview speech. According to theseexperiments, we achieved the best Word Error Rate(WER) of 20.47%."}]}, "item_1583103108160": {"attribute_name": "Keywords", "attribute_value_mlt": [{"interim": "Spontaneous speech"}, {"interim": "ASR"}, {"interim": "HMM-GMM Myanmar"}]}, "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": "Naing, Hay Mar Soe"}, {"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": "2018-02-22"}, "item_1583159847033": {"attribute_name": "Identifier", "attribute_value": "http://onlineresource.ucsy.edu.mm/handle/123456789/329"}, "item_title": "Automatic Speech Recognition on Spontaneous Interview Speech", "item_type_id": "21", "owner": "1", "path": ["1597824273898"], "permalink_uri": "http://hdl.handle.net/20.500.12678/0000004671", "pubdate": {"attribute_name": "Deposited date", "attribute_value": "2019-07-03"}, "publish_date": "2019-07-03", "publish_status": "0", "recid": "4671", "relation": {}, "relation_version_is_last": true, "title": ["Automatic Speech Recognition on Spontaneous Interview Speech"], "weko_shared_id": -1}
Automatic Speech Recognition on Spontaneous Interview Speech
http://hdl.handle.net/20.500.12678/0000004671
http://hdl.handle.net/20.500.12678/0000004671356c8c89-79b2-4d0e-9404-ce096babce09
43552e1f-8f86-43a0-afa9-ea9f4e91db8b
Publication type | ||||||
---|---|---|---|---|---|---|
Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Automatic Speech Recognition on Spontaneous Interview Speech | |||||
Language | en | |||||
Publication date | 2018-02-22 | |||||
Authors | ||||||
Naing, Hay Mar Soe | ||||||
Pa, Win Pa | ||||||
Description | ||||||
This paper presents a spontaneous speechrecognition system for Myanmar language. Automaticspeech recognition (ASR) on some controlled speechhas achieved almost human performance. However, theperformance of spontaneous speech is drasticallydecreased due to the diversity of speaking styles, speakrate, presence of additive and non-linear distortion,accents and weakened articulation. In this study, webuilt a recognizer for Myanmar Interview speech byusing the classical Gaussian Mixture Model basedHidden Markov Model (HMM-GMM) approach. Weinvested that the effect of variation on acoustic featureand number of senones and Gaussian densities onMyanmar Interview speech. According to theseexperiments, we achieved the best Word Error Rate(WER) of 20.47%. | ||||||
Keywords | ||||||
Spontaneous speech, ASR, HMM-GMM Myanmar | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/329 | |||||
Journal articles | ||||||
Sixteenth International Conferences on Computer Applications(ICCA 2018) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |