This paper describes the TALP-UPC system in the Spanish-English WMT 2016 biomedical shared task. Our system is a standard phrase-based system enhanced with vocabulary expansion using bilingual word embeddings and a characterbased neural language model with rescoring. The former focuses on resolving outof- vocabulary words, while the latter enhances the fluency of the system. The two modules progressively improve the final translation as measured by a combination of several lexical metrics.
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Costa-Jussá, M. R., España-Bonet, C., Madhyastha, P., Escolano, C., & Fonollosa, J. A. R. (2016). The TALP-UPC Spanish-English WMT Biomedical Task: Bilingual Embeddings and Char-based Neural Language Model Rescoring in a Phrase-based System. In Proceedings of the Annual Meeting of the Association for Computational Linguistics (Vol. 2, pp. 463–468). Association for Computational Linguistics (ACL). https://doi.org/10.18653/v1/w16-2336