2024-03-29T10:02:09Z
https://meral.edu.mm/oai
oai:meral.edu.mm:recid/4683
2021-12-13T04:15:04Z
1582963302567:1597824273898
user-ucsy
Statistical Machine Translation between Myanmar Sign Language and Myanmar Written Text
Moe, Swe Zin
Thu, Ye Kyaw
Hlaing, Hnin Wai Wai
Nwe, Hlaing Myat
Aung, Ni Htwe
Thant, Hnin Aye
Min, Nandar Win
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.
2018-02-22
http://hdl.handle.net/20.500.12678/0000004683
https://meral.edu.mm/records/4683