TY - GEN
T1 - Limsi @ wmt'15
T2 - 10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015
AU - Marie, Benjamin
AU - Allauzen, Alexandre
AU - Burlot, Franck
AU - Do, Quoc Khanh
AU - Ive, Julia
AU - Knyazeva, Elena
AU - Labeau, Matthieu
AU - Lavergne, Thomas
AU - Löser, Kevin
AU - Pécheux, Nicolas
AU - Yvon, François
N1 - Publisher Copyright:
© EMNLP 2015. All rights reserved.
PY - 2015/1/1
Y1 - 2015/1/1
N2 - This paper describes LIMSI's submissions to the shared WMT'15 translation task. We report results for French-English, Russian-English in both directions, as well as for Finnish-into-English. Our submissions use NCODE and MOSES along with continuous space translation models in a post-processing step. The main novelties of this year's participation are the following: For Russian-English, we investigate a tailored normalization of Russian to translate into English, and a two-step process to translate first into simplified Russian, followed by a conversion into inflected Russian. For French-English, the challenge is domain adaptation, for which only monolingual corpora are available. Finally, for the Finnish-to-English task, we explore unsupervised morphological segmentation to reduce the sparsity of data induced by the rich morphology on the Finnish side.
AB - This paper describes LIMSI's submissions to the shared WMT'15 translation task. We report results for French-English, Russian-English in both directions, as well as for Finnish-into-English. Our submissions use NCODE and MOSES along with continuous space translation models in a post-processing step. The main novelties of this year's participation are the following: For Russian-English, we investigate a tailored normalization of Russian to translate into English, and a two-step process to translate first into simplified Russian, followed by a conversion into inflected Russian. For French-English, the challenge is domain adaptation, for which only monolingual corpora are available. Finally, for the Finnish-to-English task, we explore unsupervised morphological segmentation to reduce the sparsity of data induced by the rich morphology on the Finnish side.
UR - https://www.scopus.com/pages/publications/85054959169
M3 - Conference contribution
AN - SCOPUS:85054959169
T3 - 10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Proceedings
SP - 145
EP - 151
BT - 10th Workshop on Statistical Machine Translation, WMT 2015 at the 2015 Conference on Empirical Methods in Natural Language Processing, EMNLP 2015 - Proceedings
A2 - Bojar, Ondrej
A2 - Chatterjee, Rajan
A2 - Federmann, Christian
A2 - Haddow, Barry
A2 - Hokamp, Chris
A2 - Huck, Matthias
A2 - Logacheva, Varvara
A2 - Pecina, Pavel
PB - Association for Computational Linguistics (ACL)
Y2 - 17 September 2015 through 18 September 2015
ER -