The TALP-UPC neural machine translation system for german/finnish-english using the inverse direction model in rescoring
Document typeConference lecture
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In this paper, we describe the TALP- UPC participation in the News Task for German-English and Finish-English. Our primary submission implements a fully character to character neural machine translation architecture with an additional rescoring of a n-best list of hypothesis us- ing a forced back-translation to the source sentence. This model gives consistent im- provements on different pairs of languages for the language direction with the low- est performance while keeping the qual- ity in the direction with the highest perfor- mance. Additional experiments are reported for multilingual character to character neural machine translation, phrase-based trans- lation and the additional Turkish-English language pair.
CitationEscolano, C., Ruiz, M., Fonollosa, J. A. R. The TALP-UPC neural machine translation system for german/finnish-english using the inverse direction model in rescoring. A: Conference on Empirical Methods in Natural Language Processing. "Proceedings of the Second Conference on Machine Translation". 2017, p. 283-287.