Effective Strategies in Zero-Shot Neural Machine Translation

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Authors Thanh-Le Ha, Alexander Waibel, Jan Niehues
Journal/Conference Name arXiv preprint
Paper Category
Paper Abstract In this paper, we proposed two strategies which can be applied to a multilingual neural machine translation system in order to better tackle zero-shot scenarios despite not having any parallel corpus. The experiments show that they are effective in terms of both performance and computing resources, especially in multilingual translation of unbalanced data in real zero-resourced condition when they alleviate the language bias problem.
Date of publication 2017
Code Programming Language Python
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