Machine Translation of Restaurant Reviews: New Corpus for Domain Adaptation and Robustness

October 31, 2019 ยท Declared Dead ยท ๐Ÿ› Conference on Empirical Methods in Natural Language Processing

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Authors Alexandre Bรฉrard, Ioan Calapodescu, Marc Dymetman, Claude Roux, Jean-Luc Meunier, Vassilina Nikoulina arXiv ID 1910.14589 Category cs.CL: Computation & Language Citations 29 Venue Conference on Empirical Methods in Natural Language Processing Last Checked 4 months ago
Abstract
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. We discuss the challenges of such user-generated content, and train good baseline models that build upon the latest techniques for MT robustness. We also perform an extensive evaluation (automatic and human) that shows significant improvements over existing online systems. Finally, we propose task-specific metrics based on sentiment analysis or translation accuracy of domain-specific polysemous words.
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