Demonstration of a Neural Machine Translation System with Online Learning for Translators
Miguel Domingo | Mercedes García-Martínez | Amando Estela Pastor | Laurent Bié | Alexander Helle | Álvaro Peris | Francisco Casacuberta | Manuel Herranz Pérez
Proceedings of the 57th Annual Meeting of the Association for Computational Linguistics: System Demonstrations
We present 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. We pretend to save post-editing effort as the machine is continuously learning from its mistakes and adapting the models to a specific domain or user style.
- Miguel Domingo 1
- Mercedes García-Martínez 1
- Amando Estela Pastor 1
- Laurent Bié 1
- Álvaro Peris 1
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