@inproceedings{cea804c324044f1bbec5ea7eb05869fc,
title = "NCU IISR English-Korean and English-Chinese Named Entity Transliteration Using Different Grapheme Segmentation Approaches",
abstract = "This paper describes our approach to English-Korean and English-Chinese transliteration task of NEWS 2015. We use different grapheme segmentation approaches on source and target languages to train several transliteration models based on the M2M-aligner and DirecTL+, a string transduction model. Then, we use two reranking techniques based on string similarity and web co-occurrence to select the best transliteration among the prediction results from the different models. Our English-Korean standard and non-standard runs achieve 0.4482 and 0.5067 in top-1 accuracy respectively, and our English-Chinese standard runs achieves 0.2925 in top-1 accuracy. c 2015 Association for Computational Linguistics.",
author = "Wang, {Yu Chun} and Wu, {Chun Kai} and Tsai, {Richard Tzong Han}",
note = "Publisher Copyright: {\textcopyright} 2015 Proceedings of the Annual Meeting of the Association for Computational Linguistics.; 15th Named Entity Workshop, NEWS 2015 ; Conference date: 31-07-2015",
year = "2015",
language = "???core.languages.en_GB???",
series = "Proceedings of the Annual Meeting of the Association for Computational Linguistics",
publisher = "Association for Computational Linguistics (ACL)",
pages = "83--87",
editor = "Xiangyu Duan and Banchs, {Rafael E.} and Min Zhang and Haizhou Li and A. Kumara",
booktitle = "Proceedings of the 15th Named Entity Workshop, NEWS 2015 - Held as part ACL 2015",
}