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Statistical Machine Translation between Myanmar Sign Language and Myanmar Written Text
http://hdl.handle.net/20.500.12678/0000004683
http://hdl.handle.net/20.500.12678/00000046833e535804-b275-4f3f-b666-918bf4808923
110e2fbd-2208-4d38-8408-a77ed5c1fcbf
Publication type | ||||||
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Article | ||||||
Upload type | ||||||
Publication | ||||||
Title | ||||||
Title | Statistical Machine Translation between Myanmar Sign Language and Myanmar Written Text | |||||
Language | en | |||||
Publication date | 2018-02-22 | |||||
Authors | ||||||
Moe, Swe Zin | ||||||
Thu, Ye Kyaw | ||||||
Hlaing, Hnin Wai Wai | ||||||
Nwe, Hlaing Myat | ||||||
Aung, Ni Htwe | ||||||
Thant, Hnin Aye | ||||||
Min, Nandar Win | ||||||
Description | ||||||
This paper contributes the first evaluation of the quality of automatic translation between Myanmar sign language (MSL) and Myanmar written text, in both directions. Our developing MSL-Myanmar parallel corpus was used for translations and the experiments were carried out using three different statistical machine translation (SMT) approaches: phrase-based, hierarchical phrase-based, and the operation sequence model. In addition, three different segmentation schemes were studies, these were syllable segmentation, word segmentation and sign unit based word segmentation. The results show that the highest quality machine translation was attained with syllable segmentations for both MSL and Myanmar written text. | ||||||
Keywords | ||||||
Hierarchical Phrase-based Machine Translation, Myanmar sign language, Operation Sequence Model, Phrase-based Machine Translation, Word Segmentation | ||||||
Identifier | http://onlineresource.ucsy.edu.mm/handle/123456789/346 | |||||
Journal articles | ||||||
Sixteenth International Conferences on Computer Applications(ICCA 2018) | ||||||
Conference papers | ||||||
Books/reports/chapters | ||||||
Thesis/dissertations |