In this work, we tackle the task of machine translation (MT) without parallel training data. We frame the MT problem as a decipherment task, treating the foreign text as a cipher for English and present novel methods for training translation models from nonparallel text.
Close to the methods described in this work, REF treat training and translation without parallel data as a deciphering problem.
Deciphering Foreign Language
Proceedings of the 49th Annual Meeting of the Association for Computational Linguistics: Human Language Technologies
Computer Science