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1
Few-shot learning through contextual data augmentation
In: EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics ; https://hal.inria.fr/hal-03121971 ; EACL 2021 - 16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev / Virtual, Ukraine (2021)
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2
DiaBLa: A Corpus of Bilingual Spontaneous Written Dialogues for Machine Translation
In: ISSN: 1574-020X ; EISSN: 1574-0218 ; Language Resources and Evaluation ; https://hal.inria.fr/hal-03021633 ; Language Resources and Evaluation, Springer Verlag, 2020, ⟨10.1007/s10579-020-09514-4⟩ (2020)
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Architecture of a Scalable, Secure and Resilient Translation Platform for Multilingual News Media
In: Proceedings of the 1st International Workshop on Language Technology Platforms ; 1st International Workshop on Language Technology Platforms ; https://hal.archives-ouvertes.fr/hal-02900633 ; 1st International Workshop on Language Technology Platforms, 2020, Marseille, France. pp.16-21 (2020)
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The University of Edinburgh’s English-Tamil and English-Inuktitut Submissions to the WMT20 News Translation Task
In: Proceedings of the 5th Conference on Machine Translation ; 5th Conference on Machine Translation ; https://hal.archives-ouvertes.fr/hal-02981153 ; 5th Conference on Machine Translation, Nov 2020, Online, Unknown Region (2020)
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Findings of the WMT 2020 Biomedical Translation Shared Task: Basque, Italian and Russian as New Additional Languages
In: Proceedings of the 5th Conference on Machine Translation ; 5th Conference on Machine Translation ; https://hal.inria.fr/hal-02986356 ; 5th Conference on Machine Translation, 2020, Online, Unknown Region (2020)
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The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task
In: Proceedings of the 5th Conference on Machine Translation ; 5th Conference on Machine Translation ; https://hal.archives-ouvertes.fr/hal-02981159 ; 5th Conference on Machine Translation, Nov 2020, Online, Unknown Region (2020)
Abstract: International audience ; This paper describes the joint submission of the University of Edinburgh and Uppsala University to the WMT'20 chat translation task for both language directions (English↔German). We use existing state-of-the-art machine translation models trained on news data and fine-tune them on in-domain and pseudo-in-domain web crawled data. We also experiment with (i) adaptation using speaker and domain tags and (ii) using different types and amounts of preceding context. We observe that contrarily to expectations, exploiting context degrades the results (and on analysis the data is not highly contextual). However using domain tags does improve scores according to the automatic evaluation. Our final primary systems use domain tags and are ensembles of 4 models, with noisy channel reranking of outputs. Our en-de system was ranked second in the shared task while our de-en system outperformed all the other systems.
Keyword: [INFO.INFO-CL]Computer Science [cs]/Computation and Language [cs.CL]; Chat; Context; Dialogue; Domain adaptation; English; German; Machine translation; Shared task
URL: https://hal.archives-ouvertes.fr/hal-02981159
https://hal.archives-ouvertes.fr/hal-02981159/file/WMT_2020_Chat.pdf
https://hal.archives-ouvertes.fr/hal-02981159/document
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7
Going beyond the sentence : Contextual Machine Translation of Dialogue ; Au-delà de la phrase : traduction automatique de dialogue en contexte
Bawden, Rachel. - : HAL CCSD, 2018
In: https://tel.archives-ouvertes.fr/tel-02004683 ; Computation and Language [cs.CL]. Université Paris Saclay (COmUE), 2018. English. ⟨NNT : 2018SACLS524⟩ (2018)
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8
Machine Translation, it’s a question of style, innit? The case of English tag questions
In: Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing ; Conference on Empirical Methods in Natural Language Processing (EMNLP 2017) ; https://hal.archives-ouvertes.fr/hal-01588171 ; Conference on Empirical Methods in Natural Language Processing (EMNLP 2017), Sep 2017, Copenhague, Denmark. pp.2497-2502 ; http://emnlp2017.net/ (2017)
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