@InProceedings{myatmon-EtAl:2020:LREC,
  author    = {Myat Mon, Aye  and  Ding, Chenchen  and  Kaing, Hour  and  Mar Soe, Khin  and  Utiyama, Masao  and  Sumita, Eiichiro},
  title     = {A Myanmar (Burmese)-English Named Entity Transliteration Dictionary},
  booktitle      = {Proceedings of The 12th Language Resources and Evaluation Conference},
  month          = {May},
  year           = {2020},
  address        = {Marseille, France},
  publisher      = {European Language Resources Association},
  pages     = {2980--2983},
  abstract  = {Transliteration is generally a phonetically based transcription across different writing systems. It is a crucial task for various downstream natural language processing applications. For the Myanmar (Burmese) language, robust automatic transliteration for borrowed English words is a challenging task because of the complex Myanmar writing system and the lack of data. In this study, we constructed a Myanmar-English named entity dictionary containing more than eighty thousand transliteration instances. The data have been released under a CC BY-NC-SA license. We evaluated the automatic transliteration performance using statistical and neural network-based approaches based on the prepared data. The neural network model outperformed the statistical model significantly in terms of the BLEU score on the character level. Different units used in the Myanmar script for processing were also compared and discussed.},
  url       = {https://www.aclweb.org/anthology/2020.lrec-1.364}
}