Zobrazeno 1 - 10
of 32
pro vyhledávání: '"Rachel Bawden"'
Publikováno v:
Computational Linguistics, Vol 48, Iss 3 (2022)
We present a survey covering the state of the art in low-resource machine translation (MT) research. There are currently around 7,000 languages spoken in the world and almost all language pairs lack significant resources for training machine translat
Externí odkaz:
https://doaj.org/article/c67ef92aeb924e50a96fada3b039dfa7
Autor:
Rachel Bawden
Publikováno v:
Computational Linguistics, Vol 47, Iss 3, Pp 703-705 (2021)
Externí odkaz:
https://doaj.org/article/8842787f061f4c51833d9b37f9aa26a5
L’abandon des systèmes graphiques au profit de l’orthographe contemporaine dans l’écrasante majorité des éditions de textes du xviie siècle. a fait disparaître leur richesse graphématique. Cette dernière est logiquement restée en grand
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::67304656c3417553b59aa6803e12ef90
http://journals.openedition.org/linx/9346
http://journals.openedition.org/linx/9346
Autor:
Simon Gabay, Pedro Ortiz Suarez, Rachel Bawden, Alexandre Bartz, Philippe Gambette, Benoît Sagot
Publikováno v:
Actes de la 29e Conférence sur le Traitement Automatique des Langues Naturelles. Volume 1 : conférence principale
TALN 2022-Traitement Automatique des Langues Naturelles
TALN 2022-Traitement Automatique des Langues Naturelles, Jun 2022, Avignon, France. pp.154-165
HAL
TALN 2022-Traitement Automatique des Langues Naturelles
TALN 2022-Traitement Automatique des Langues Naturelles, Jun 2022, Avignon, France. pp.154-165
HAL
National audience; Despite their undoubted quality, the resources and tools available for the analysis of Ancien Régime French are no longer able to meet the challenges of research in linguistics and literature for this period. After having precisel
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::8819e462a85e8d0caac0da96bb70f57c
https://hal.science/hal-03701524/file/9987.pdf
https://hal.science/hal-03701524/file/9987.pdf
Publikováno v:
Language Resources and Evaluation
Language Resources and Evaluation, Springer Verlag, 2020, ⟨10.1007/s10579-020-09514-4⟩
Language Resources and Evaluation, Springer Verlag, 2020, ⟨10.1007/s10579-020-09514-4⟩
We present a new English–French dataset for the evaluation of Machine Translation (MT) for informal, written bilingual dialogue. The test set contains 144 spontaneous dialogues (5700+ sentences) between native English and French speakers, mediated
Autor:
Alexandre Bartz, Juliette Janes, Laurent Romary, Philippe Gambette, Rachel Bawden, Pedro Ortiz Suarez, Benoît Sagot, Simon Gabay
Publikováno v:
Next Gen TEI, 2021-TEI Conference and Members’ Meeting
Next Gen TEI, 2021-TEI Conference and Members’ Meeting, Oct 2021, Virtual, United States
HAL
Next Gen TEI, 2021-TEI Conference and Members’ Meeting, Oct 2021, Virtual, United States
HAL
International audience
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::2b75697bc64e27379beb6a6cb784153c
https://hal.archives-ouvertes.fr/hal-03380805
https://hal.archives-ouvertes.fr/hal-03380805
Publikováno v:
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Aug 2021, Bangkok, Thailand
ACL/IJCNLP (Findings)
HAL
ACL-IJCNLP 2021-Findings of the Association for Computational Linguistics
ACL-IJCNLP 2021-Findings of the Association for Computational Linguistics, Aug 2021, Bangkok, Thailand
Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021, Aug 2021, Bangkok, Thailand
ACL/IJCNLP (Findings)
HAL
ACL-IJCNLP 2021-Findings of the Association for Computational Linguistics
ACL-IJCNLP 2021-Findings of the Association for Computational Linguistics, Aug 2021, Bangkok, Thailand
International audience; Cognate prediction is the task of generating, in a given language, the likely cognates of words in a related language, where cognates are words in related languages that have evolved from a common ancestor word. It is a task f
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::e7cbe8eee13ca55157c5c2bb1a4e5f09
https://hal.inria.fr/hal-03243380/file/Is_Cognate_Prediction_a_Low_Resource_Machine_Translation_Task__ACL2021Findings-2.pdf
https://hal.inria.fr/hal-03243380/file/Is_Cognate_Prediction_a_Low_Resource_Machine_Translation_Task__ACL2021Findings-2.pdf
Publikováno v:
Artaud, F, Bawden, R & Birch, A 2021, Few-shot learning through contextual data augmentation . in Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume . pp. 1049-1062, 16th conference of the European Chapter of the Association for Computational Linguistics, Virtual Conference, 19/04/21 . < https://www.aclweb.org/anthology/2021.eacl-main.90 >
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev / Virtual, Ukraine
EACL
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics
EACL 2021-16th Conference of the European Chapter of the Association for Computational Linguistics, Apr 2021, Kiev / Virtual, Ukraine
EACL
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: Main Volume
Machine translation (MT) models used in industries with constantly changing topics, such as translation or news agencies, need to adapt to new data to maintain their performance over time. Our aim is to teach a pre-trained MT model to translate previ
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::94ad60a0b4a98c5716a2a374bad42395
https://www.pure.ed.ac.uk/ws/files/208727159/Few_shot_learning_ARTAUD_DOA01022021_VOR_CC_BY.pdf
https://www.pure.ed.ac.uk/ws/files/208727159/Few_shot_learning_ARTAUD_DOA01022021_VOR_CC_BY.pdf
Publikováno v:
Proceedings of the 5th Conference on Machine Translation
5th Conference on Machine Translation
5th Conference on Machine Translation, Nov 2020, Online, Unknown Region
Moghe, N, Hardmeier, C & Bawden, R 2020, The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task . in Proceedings of the Fifth Conference on Machine Translation . pp. 473-478, Fifth Conference on Machine Translation, Online Conference, 19/11/20 . < https://www.aclweb.org/anthology/2020.wmt-1.58 >
HAL
5th Conference on Machine Translation
5th Conference on Machine Translation, Nov 2020, Online, Unknown Region
Moghe, N, Hardmeier, C & Bawden, R 2020, The University of Edinburgh-Uppsala University’s Submission to the WMT 2020 Chat Translation Task . in Proceedings of the Fifth Conference on Machine Translation . pp. 473-478, Fifth Conference on Machine Translation, Online Conference, 19/11/20 . < https://www.aclweb.org/anthology/2020.wmt-1.58 >
HAL
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 tran
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=dedup_wf_001::542af568cab72993aca040648281df66
https://hal.archives-ouvertes.fr/hal-02981159/document
https://hal.archives-ouvertes.fr/hal-02981159/document
Publikováno v:
Bawden, R, Zhang, B, Yankovskaya, L, Tättar, A & Post, M 2020, A Study in Improving BLEU Reference Coverage with Diverse Automatic Paraphrasing . in Findings of the Association for Computational Linguistics: EMNLP 2020 . pp. 918-932, The 2020 Conference on Empirical Methods in Natural Language Processing, Virtual conference, 16/11/20 . < https://www.aclweb.org/anthology/2020.findings-emnlp.82 >
EMNLP (Findings)
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings
2020 Conference on Empirical Methods in Natural Language Processing: Findings
2020 Conference on Empirical Methods in Natural Language Processing: Findings, 2020, Punta Cana (online), Dominican Republic
Findings of the Association for Computational Linguistics: EMNLP 2020
HAL
EMNLP (Findings)
Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing: Findings
2020 Conference on Empirical Methods in Natural Language Processing: Findings
2020 Conference on Empirical Methods in Natural Language Processing: Findings, 2020, Punta Cana (online), Dominican Republic
Findings of the Association for Computational Linguistics: EMNLP 2020
HAL
We investigate a long-perceived shortcoming in the typical use of BLEU: its reliance on a single reference. Using modern neural paraphrasing techniques, we study whether automatically generating additional diverse references can provide better covera
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::87173cd05b698e7ae5eaf8d093ac3ca9
https://www.pure.ed.ac.uk/ws/files/174905090/ParBleu_Syntactic_diversity_26.pdf
https://www.pure.ed.ac.uk/ws/files/174905090/ParBleu_Syntactic_diversity_26.pdf