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1
Automatic Extraction of Verb Paradigms in Regional Languages: the case of the Linguistic Crescent varieties
In: STLU (Spoken Language Technologies for Under-resourced languages) ; https://halshs.archives-ouvertes.fr/halshs-02508210 ; STLU (Spoken Language Technologies for Under-resourced languages), European Language Resources Association (ELRA), Jan 2020, Marseille, France. pp.245-249 ; https://lrec2020.lrec-conf.org/en/ (2020)
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Automatic Extraction of Verb Paradigms in Regional Languages: the case of the Linguistic Crescent varieties
In: STLU (Spoken Language Technologies for Under-resourced languages) ; https://halshs.archives-ouvertes.fr/halshs-02508210 ; STLU (Spoken Language Technologies for Under-resourced languages), European Language Resources Association (ELRA), Jan 2020, Marseille, France. pp.245-249 ; https://lrec2020.lrec-conf.org/en/ (2020)
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3
LIMSI@WMT16: Machine Translation of News
In: First Conference on Machine Translation ; https://hal.archives-ouvertes.fr/hal-01388659 ; First Conference on Machine Translation, Aug 2016, Berlin, Germany. pp.239--245, ⟨10.18653/v1/W16-2304⟩ ; https://statmt.org/wmt16 (2016)
Abstract: International audience ; This paper describes LIMSI’s submissions to the shared WMT’16 task “Translation of News”. We report results for Romanian-English in both directions, for English to Russian, as well as preliminary experiments on reordering to translate from English into German. Our submissions use mainly NCODE and MOSES along with continuous space models in a post-processing step. The main novelties of this year’s participation are the following: for the translation into Russian and Romanian, we have attempted to extend the output of the decoder with morphological variations and to use a CRF model to rescore this new search space; as for the translation into German, we have been experimenting with source-side pre-ordering based on a dependency structure allowing permutations in order to reproduce the tar- get word order.
Keyword: [INFO.INFO-AI]Computer Science [cs]/Artificial Intelligence [cs.AI]; Machine translation; Machine translation evaluation
URL: https://doi.org/10.18653/v1/W16-2304
https://hal.archives-ouvertes.fr/hal-01388659/document
https://hal.archives-ouvertes.fr/hal-01388659
https://hal.archives-ouvertes.fr/hal-01388659/file/W16-2304.pdf
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4
Two-Step MT: Predicting Target Morphology
In: International Workshop on Spoken Language Translation ; https://hal.archives-ouvertes.fr/hal-01592337 ; International Workshop on Spoken Language Translation, 2016, Seattle, WA, United States (2016)
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5
The QT21/HimL Combined Machine Translation System
Braune, Fabienne; Yvon, François; Blain, Frédéric. - : Association for Computational Linguistics, 2016
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6
The QT21/HimL combined machine translation system
Ney, Hermann; Lavergne, Thomas; Tamchyna, Aleš. - : Association for Computational Linguistics, 2016
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7
LIMSIWMT'15 : Translation Task
Marie, Benjamin [Verfasser]; Allauzen, Alexandre [Verfasser]; Burlot, Franck [Verfasser]. - Aachen : Universitätsbibliothek der RWTH Aachen, 2015
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8
LIMSI$@$WMT'15 : Translation Task
In: Proceedings of the Tenth Workshop on Statistical Machine Translation ; https://hal.archives-ouvertes.fr/hal-02912383 ; Proceedings of the Tenth Workshop on Statistical Machine Translation, Sep 2015, Lisbon, Portugal. pp.145-151, ⟨10.18653/v1/W15-3016⟩ (2015)
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9
Apprentissage partiellement supervisé d'un étiqueteur morpho-syntaxique par transfert cross-lingue
In: Conférence sur le Traitement Automatique des Langues Naturelles ; https://hal.archives-ouvertes.fr/hal-01908360 ; Conférence sur le Traitement Automatique des Langues Naturelles, Jan 2014, Marseille, France (2014)
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