Demonstration of a Neural Machine Translation System with Online Learning for Translators

06/21/2019

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by   Miguel Domingo, et al.

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Pangeanic

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Universitat Politècnica de València

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We introduce a demonstration of our system, which implements online learning for neural machine translation in a production environment. These techniques allow the system to continuously learn from the corrections provided by the translators. We implemented an end-to-end platform integrating our machine translation servers to one of the most common user interfaces for professional translators: SDL Trados Studio. Our objective was to save post-editing effort as the machine is continuously learning from human choices and adapting the models to a specific domain or user style.