Abstract
Despite SMT (Statistical Machine Translation) recently revolutionised MT for major language pairs, when addressing under-resourced and, to some extent, mildly-resourced languages, it still faces some difficulties such as the need of important quantities of parallel texts, the limited guaranty of the quality, etc. We thus speculate that RBMT (Rule Based Machine Translation) can fill the gap for these languages.
Cite
CITATION STYLE
de Malézieux, G., Bosc, A., & Berment, V. (2014). RBMT as an alternative to SMT for under-resourced languages. In Proceedings of the Conference - 5th Workshop on South and Southeast Asian NLP, WSSANLP 2014 - co-located with the 25th International Conference on Computational Linguistics, COLING 2014 (pp. 50–54). Association for Computational Linguistics (ACL). https://doi.org/10.3115/v1/w14-5507
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