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Item

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  1. Myanmar Institute of Information Technology
  1. Myanmar Institute of Information Technology
  2. Faculty of Computer Science

Statistical Machine Translation between Myanmar Sign Language and Myanmar SignWriting

http://hdl.handle.net/20.500.12678/0000007672
http://hdl.handle.net/20.500.12678/0000007672
e2babcc6-8106-45fe-9c08-26f5c3494699
cef27ac2-0593-41f7-ba09-29c0d721aeda
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Statistical Statistical Machine Translation between Myanmar Sign Language and Myanmar SignWriting.pdf (3 MB)
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Publication type
Journal article
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Publication
Title
Title Statistical Machine Translation between Myanmar Sign Language and Myanmar SignWriting
Language en
Publication date 2018-03-06
Authors
Hnin Wai Wai Hlaing
Ye Kyaw Thu
Swe Zin Moe
Hlaing Myat Nwe
Ni Htwe Aung
Nandar Win Min
Hnin Aye Thant
Description
This paper contributes the first evaluation of automatic machine translation between Myanmar Sign Language (MSL) and Myanmar SignWriting (MSW). The main motivation is to introduce SignWriting
to the Myanmar Deaf society with the help of statistical machine translation. In this paper, we use our MSL-MSW corpus for general domain that contains a textual representation of MSL and its equivalent Myanmar
SignWriting. The methods studied in this work were phrase-based, hierarchical phrase-based and the operation sequence model. In addition, two different segmentation schemes were studies, these were syllable segmentation and word segmentation for MSL. The
performance of the machine translation systems was automatically measured in terms of BLEU and RIBES for all experiments. Our main findings were that operation sequence model gave the highest scores (37.54 BLEU and 0.8280 RIBES) for MSL to MSW translation and hierarchical phrase based machine translation gave the highest scores (52.79 BLEU and 0.8756 RIBES) for MSW to MSL translation. Generally, translation with word segmented MSL achieved better performance
than syllable segmentation of MSL. Our 10-fold cross validation results produced promising results even with the limited training data and we expect this can be developed into a useful machine translation system as
more data becomes available in the future.
Keywords
Machine Translation, Hierarchical Phrase-based Machine Translation (HPBSMT), Myanmar Sign Language (MSL), Myanmar SignWriting (MSW), Operation Sequence Model (OSM), Phrasebased Machine Translation (PBSMT)
Journal articles
Pages 65-72
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