Abstract
We report the results of our experiments in the context of the NEWS 2015 Shared Task on Transliteration. We focus on methods of combining multiple base systems, and leveraging transliterations from multiple languages. We show error reductions over the best base system of up to 10% when using supplemental transliterations, and up to 20% when using system combination. We also discuss the quality of the shared task datasets. c 2015 Association for Computational Linguistics.
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CITATION STYLE
Nicolai, G., Hauer, B., Salameh, M., Arnaud, A. S., Xu, Y., Yao, L., & Kondrak, G. (2015). Multiple System Combination for Transliteration. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 2015-July, pp. 72–77). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w15-3911
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