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Simple Search
Hits 1 – 18 of 18
1
Joint WMT 2012 Submission of the QUAERO Project
Le, Hai-son
;
Lavergne, Thomas
;
Freitag, Markus
. - : Association for Computational Linguistics, 2022
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2
Joint WMT Submission of the QUAERO Project
Ney, Hermann
;
Senellart, Jean
;
Crego, Josep Maria
. - : Association for Computational Linguistics, 2022
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3
Boosting Neural Machine Translation with Similar Translations
Xu, Jitao
;
Crego, Josep-Maria
;
Senellart, Jean
In: Annual Meeting of the Association for Computational Linguistics ; https://hal.archives-ouvertes.fr/hal-02956324 ; Annual Meeting of the Association for Computational Linguistics, Jul 2020, Seattle, United States. pp.1570-1579, ⟨10.18653/v1/2020.acl-main.143⟩ (2020)
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4
Integrating Domain Terminology into Neural Machine Translation ...
The 28th International Conference on Computational Linguistics 2020
;
CREGO, Josep
;
Michon, Elise
. - : Underline Science Inc., 2020
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5
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation
Pham, Minh Quang
;
Crego, Josep-Maria
;
Yvon, François
...
In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-02343215 ; International Workshop on Spoken Language Translation, Nov 2019, Hong-Kong, China. ⟨10.5281/zenodo.3524978⟩ ; https://zenodo.org/communities/iwslt2019/ (2019)
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6
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation ...
Pham, MinhQuang
;
Crego, Josep
;
Yvon, François
;
Senellart, Jean
. - : Zenodo, 2019
Abstract:
Supervised machine translation works well when the train and test data are sampled from the same distribution. When this is not the case, adaptation techniques help ensure that the knowledge learned from out-of-domain texts generalises to in-domain sentences. We study here a related setting, multi-domain adaptation, where the number of domains is potentially large and adapting separately to each domain would waste training resources. Our proposal transposes to neural machine translation the feature expansion technique of (Daumé III, 2007): it isolates domain-agnostic from domain-specific lexical representations, while sharing the most of the network across domains. Our experiments use two architectures and two language pairs: they show that our approach, while simple and computationally inexpensive, outperforms several strong baselines and delivers a multi-domain system that successfully translates texts from diverse sources. ...
URL:
https://zenodo.org/record/3524978
https://dx.doi.org/10.5281/zenodo.3524978
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7
Lexical Micro-adaptation for Neural Machine Translation ...
Xu, Jitao
;
Crego, Josep
;
Senellart, Jean
. - : Zenodo, 2019
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8
Lexical Micro-adaptation for Neural Machine Translation ...
Xu, Jitao
;
Crego, Josep
;
Senellart, Jean
. - : Zenodo, 2019
BASE
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9
Generic and Specialized Word Embeddings for Multi-Domain Machine Translation ...
Pham, MinhQuang
;
Crego, Josep
;
Yvon, François
. - : Zenodo, 2019
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10
Fixing Translation Divergences in Parallel Corpora for Neural MT
Pham, Minh Quang
;
Crego, Josep-Maria
;
Senellart, Jean
...
In: Proceedings of the 2018 Conference on Empirical Methods in Natural Language Processing ; Conference on Empirical Methods in Natural Language Processing ; https://hal.archives-ouvertes.fr/hal-01908309 ; Conference on Empirical Methods in Natural Language Processing, Nov 2018, Bruxelles, Belgium. pp.2967 - 2973 (2018)
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11
SYSTRAN Participation to the WMT2018 Shared Task on Parallel Corpus Filtering
Pham, MinhQuang
;
Crego, Josep
;
Sénellart, Jean
In: Proceedings of the Third Conference on Machine Translation: Shared Task Papers ; https://hal.archives-ouvertes.fr/hal-02315344 ; Proceedings of the Third Conference on Machine Translation: Shared Task Papers, Oct 2018, Belgium, France. pp.934-938, ⟨10.18653/v1/W18-6485⟩ (2018)
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12
Neural Machine Translation from Simplified Translations ...
Crego, Josep
;
Senellart, Jean
. - : arXiv, 2016
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13
Collaborative Machine Translation Service for Scientific texts
Lambert, Patrik
;
Senellart, Jean
;
Romary, Laurent
...
In: Proc. of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL) ; https://hal.inria.fr/hal-00723349 ; Proc. of the Demonstrations at the 13th Conference of the European Chapter of the Association for Computational Linguistics (EACL), 2012, Avignon, France. pp.11-15 (2012)
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14
Incremental adaptation using translation informations and post-editing analysis
Blain, Frederic
;
Schwenk, Holger
;
Senellart, Jean
In: 234 ; 241 (2012)
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15
Collaborative machine translation service for scientific texts
Lambert, Patrik
;
Lopez, Patrice
;
Zipser, Florian
...
In: 11 ; 15 (2012)
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16
SMT and SPE Machine Translation Systems for WMT'09
Schwenk, Holger
;
Abdul-Rauf, Sadaf
;
Barrault, Loïc
...
In: Proceedings of the Fourth Workshop on Statistical Machine Translation ; Fourth Workshop on Statistical Machine Translation ; https://hal.archives-ouvertes.fr/hal-00424686 ; Fourth Workshop on Statistical Machine Translation, Mar 2009, Athens, Greece. pp.130--134 (2009)
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17
XML Translation Workflow
Sénellart, Jean
;
Boitet, Christian
;
Romary, Laurent
In: Machine Translation Summit IX ; https://hal.inria.fr/inria-00487747 ; Machine Translation Summit IX, Sep 2003, New Orleans, United States (2003)
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18
Reconnaissance automatique des entrées du lexique-grammaire des phrases figées
Senellart, Jean
In:
Travaux de linguistique. - Liège : De Boeck Supérieure
(1998) 37, 109-125
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