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Found 7 papers, 2 papers with code
Multilingual Unsupervised Neural Machine Translation with Denoising Adapters
We consider the problem of multilingual unsupervised machine translation, translating to and from languages that only have monolingual data by using auxiliary parallel language pairs.
Multilingual Domain Adaptation for NMT: Decoupling Language and Domain Information with Adapters
In this work we study the compositionality of language and domain adapters in the context of Machine Translation.
A Multilingual Neural Machine Translation Model for Biomedical Data
We release a multilingual neural machine translation model, which can be used to translate text in the biomedical domain.
Naver Labs Europe's Systems for the Document-Level Generation and Translation Task at WNGT 2019
To address these challenges, we propose to leverage data from both tasks and do transfer learning between MT, NLG, and MT with source-side metadata (MT+NLG).
Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness
We share a French-English parallel corpus of Foursquare restaurant reviews (https://europe. naverlabs. com/research/natural-language-processing/machine-translation-of-restaurant-reviews), and define a new task to encourage research on Neural Machine Translation robustness and domain adaptation, in a real-world scenario where better-quality MT would be greatly beneficial.
Naver Labs Europe's Systems for the WMT19 Machine Translation Robustness Task
This paper describes the systems that we submitted to the WMT19 Machine Translation robustness task.
End-to-End Automatic Speech Translation of Audiobooks
We investigate end-to-end speech-to-text translation on a corpus of audiobooks specifically augmented for this task.
