Abstract
Alexandre Berard, Ioan Calapodescu, Claude Roux |
Fourth Conference on Machine Translation (WMT19), Florence, Italy, 1-2 August, 2019 |
@InProceedings{berard:2019:WMT, author = {Berard, Alexandre and Calapodescu Ioan and Roux, Claude}, title = {{NAVER LABS Europe’s Systems for the WMT19 Machine Translation Robustness Task}}, booktitle = {Proceedings of the Fourth Conference on Machine Translation, Volume 2: Shared Task Papers}, month = {August}, year = {2019}, address = {Florence, Italy}, publisher = {Association for Computational Linguistics} }
Abstract
This paper describes the systems that we submitted to the WMT19 Machine Translation robustness task. This task aims to improve MT’s robustness to noise found on social media, like informal language, spelling mistakes and other orthographic variations. The organizers provide parallel data extracted from a social media website in two language pairs: French-English and Japanese-English (in both translation directions). The goal is to obtain the best scores on unseen test sets from the same source, according to automatic metrics (BLEU) and human evaluation.
We proposed one single and one ensemble system for each translation direction. Our ensemble models ranked first in all language pairs, according to BLEU evaluation. We discuss the pre-processing choices that we made, and present our solutions for robustness to noise and domain adaptation.
FOURTH CONFERENCE ON MACHINE TRANSLATION (WMT19), August 1-2, 2019, Florence, Italy
Details on the gender equality index score 2023 (related to year 2022) for NAVER France of 81/100.
NAVER France targets are as follows:
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Index NAVER France de l’égalité professionnelle entre les femmes et les hommes pour l’année 2023 au titre des données 2022 : 81/100
Détail des indicateurs :
Les objectifs de progression de NAVER France sont :
NAVER LABS Europe 6-8 chemin de Maupertuis 38240 Meylan France Contact
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