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

Neural Machine Translation between Myanmar Sign Language and Myanmar Written Text

http://hdl.handle.net/20.500.12678/0000007669
http://hdl.handle.net/20.500.12678/0000007669
72c3334a-3b73-4bc6-b93a-88f4443c4ccb
8e1ce4f7-06e1-4030-8d98-de299c90c70e
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Neural Neural Machine Translation between Myanmar Sign Language and Myanmar Written Text.pdf (323 KB)
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Title
Title Neural Machine Translation between Myanmar Sign Language and Myanmar Written Text
Language en
Publication date 2018-12-18
Authors
Swe Zin Moe
Ye Kyaw Thu
Hnin Aye Thant
Nandar Win Min
Description
We explore Neural Machine Translation (NMT) between Myanmar Sign Language (MSL) and Myanmar Written Text (MWT). Our developing MSL-MWT parallel corpus was used and the experiments were carried
out using three different NMT approaches: Recurrent Neural Network (RNN), Trasformer, and the Convolutional Neural Network (CNN). In addition, four different segmentation schemes for word embedding
were studies, these were syllable segmentation, word segmentation (sign unit based word segmentation for MSL), SentencePiece and the Byte-Pair-Encoding (BPE). The results show that the highest quality NMT and Statistical Machine Translation (SMT) performances
were attained with syllable segmentation for both MSL and MWT. We
found that Transformer outperformed both CNN and RNN for MWT-to-MSL and MSLto-MWT translation tasks.
Keywords
Neural Machine Translation (NMT), Myanmar Sign Language (MSL), Recurrent Neural Network (RNN), Convolutional Neural Network (CNN), Byte-Pair- Encoding (BPE)
Journal articles
Neural Machine Translation between Myanmar Sign Language and Myanmar Written Text
In the second Regional Conference on Optical character recognition and Natural language processing technologies for ASEAN languages 2018 (ONA 2018)
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