Zobrazeno 1 - 10
of 295
pro vyhledávání: '"Barry Haddow"'
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:
Arturo Oncevay, Duygu Ataman, Niels van Berkel, Barry Haddow, Alexandra Birch, Johannes Bjerva
Publikováno v:
Oncevay, A, Ataman, D, van Berkel, N, Haddow, B, Birch, A & Bjerva, J 2022, Quantifying Synthesis and Fusion and their Impact on Machine Translation . in NAACL 2022-2022 Conference of the North American Chapter of the Association for Computational Linguistics : Human Language Technologies, Proceedings of the Conference . Association for Computational Linguistics, NAACL 2022-2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, Proceedings of the Conference, pp. 1308-1321, 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies, NAACL 2022, Seattle, United States, 10/07/2022 . https://doi.org/10.18653/v1/2022.naacl-main.94
Aalborg University
Oncevay, A, Ataman, D, van Berkel, N, Haddow, B, Birch-Mayne, A & Bjerva, J 2022, Quantifying Synthesis and Fusion and their Impact on Machine Translation . in M Carpuat, M-C de Marneffe & I V Meza Ruiz (eds), Proceedings of The 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Stroudsburg, PA, USA, pp. 1308-1321, 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Seattle, Washington, United States, 10/07/22 . < https://aclanthology.org/2022.naacl-main.94 >
Aalborg University
Oncevay, A, Ataman, D, van Berkel, N, Haddow, B, Birch-Mayne, A & Bjerva, J 2022, Quantifying Synthesis and Fusion and their Impact on Machine Translation . in M Carpuat, M-C de Marneffe & I V Meza Ruiz (eds), Proceedings of The 2022 Conference of the North American Chapter of the Association for Computational Linguistics: Human Language Technologies . Stroudsburg, PA, USA, pp. 1308-1321, 2022 Annual Conference of the North American Chapter of the Association for Computational Linguistics, Seattle, Washington, United States, 10/07/22 . < https://aclanthology.org/2022.naacl-main.94 >
Theoretical work in morphological typology offers the possibility of measuring morphological diversity on a continuous scale. However, literature in Natural Language Processing (NLP) typically labels a whole language with a strict type of morphology,
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::fb4f9559f270b739a716dc0225b4503b
https://vbn.aau.dk/da/publications/37d74745-ba23-4e18-a0c1-c1231fb72bf2
https://vbn.aau.dk/da/publications/37d74745-ba23-4e18-a0c1-c1231fb72bf2
Autor:
Philip Williams, Barry Haddow
Publikováno v:
First Shared Task on Automatic Minuting at Interspeech 2021.
Autor:
Alexandra Birch, Barry Haddow, Antonio Valerio Miceli Barone, Jindrich Helcl, Jonas Waldendorf, Felipe Sánchez Martínez, Mikel Forcada, Víctor Sánchez Cartagena, Juan Antonio Pérez-Ortiz, Miquel Esplà-Gomis, Wilker Aziz, Lina Murady, Sevi Sariisik, Peggy van der Kreeft, Kay Macquarrie
Publikováno v:
ZENODO
In the media industry and the focus of global reporting can shift overnight. There is a compelling need to be able to develop new machine translation systems in a short period of time and in order to more efficiently cover quickly developing stories.
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::6a1f77f54eb25cbb9c9310eae74c0c7b
https://doi.org/10.5281/zenodo.6580252
https://doi.org/10.5281/zenodo.6580252
Publikováno v:
Sen, S, Germann, U & Haddow, B 2021, The University of Edinburgh's Submission to the IWSLT21 Simultaneous Translation Task . in Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021) . pp. 46-51, 18th International Conference on Spoken Language Translation, 5/08/21 . https://doi.org/10.18653/v1/2021.iwslt-1.4
Proceedings of the 18th International Conference on Spoken Language Translation
Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)
IWSLT
Proceedings of the 18th International Conference on Spoken Language Translation
Proceedings of the 18th International Conference on Spoken Language Translation (IWSLT 2021)
IWSLT
We describe our submission to the IWSLT 2021 shared task on simultaneous text-to-text English-German translation. Our system is based on the re-translation approach where the agent re-translates the whole source prefix each time it receives a new sou
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::ec8448842ccb545f58612322d3b7af78
https://hdl.handle.net/20.500.11820/7f2f6b53-b4e4-4e4f-bf69-ff4771f3f674
https://hdl.handle.net/20.500.11820/7f2f6b53-b4e4-4e4f-bf69-ff4771f3f674
Publikováno v:
ACL/IJCNLP (Findings)
Baziotis, C, Titov, I, Birch, A & Haddow, B 2021, Exploring Unsupervised Pretraining Objectives for Machine Translation . in C Zong, F Xia, W Li & R Navigli (eds), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 . pp. 2956-2971, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Bangkok, Thailand, 1/08/21 . https://doi.org/10.18653/v1/2021.findings-acl.261
Baziotis, C, Titov, I, Birch, A & Haddow, B 2021, Exploring Unsupervised Pretraining Objectives for Machine Translation . in C Zong, F Xia, W Li & R Navigli (eds), Findings of the Association for Computational Linguistics: ACL-IJCNLP 2021 . pp. 2956-2971, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Bangkok, Thailand, 1/08/21 . https://doi.org/10.18653/v1/2021.findings-acl.261
Unsupervised cross-lingual pretraining has achieved strong results in neural machine translation (NMT), by drastically reducing the need for large parallel data. Most approaches adapt masked-language modeling (MLM) to sequence-to-sequence architectur
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::4d828f3a5772b223d955edaa60d4e91a
http://arxiv.org/abs/2106.05634
http://arxiv.org/abs/2106.05634
Publikováno v:
The Routledge Handbook of Translation and Health ISBN: 9781003167983
Machine translation has enormous potential to improve communication across language barriers in the healthcare setting. We first explain what machine translation (MT) is, and why it has the potential to be useful in the health domain. We provide a br
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_________::81d17775c094ab8d5046caca6ba57db8
https://doi.org/10.4324/9781003167983-10
https://doi.org/10.4324/9781003167983-10
Publikováno v:
ACL/IJCNLP (1)
Zhang, B, Titov, I, Haddow, B & Sennrich, R 2021, Beyond Sentence-Level End-to-End Speech Translation: Context Helps . in Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) . Online, pp. 2566-2578, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Bangkok, Thailand, 1/08/21 . https://doi.org/10.18653/v1/2021.acl-long.200
Zhang, B, Titov, I, Haddow, B & Sennrich, R 2021, Beyond Sentence-Level End-to-End Speech Translation: Context Helps . in Proceedings of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing (Volume 1: Long Papers) . Online, pp. 2566-2578, The Joint Conference of the 59th Annual Meeting of the Association for Computational Linguistics and the 11th International Joint Conference on Natural Language Processing, Bangkok, Thailand, 1/08/21 . https://doi.org/10.18653/v1/2021.acl-long.200
Document-level contextual information has shown benefits to text-based machine translation, but whether and how context helps end-to-end (E2E) speech translation (ST) is still under-studied. We fill this gap through extensive experiments using a simp
Autor:
Jonáš Kratochvíl, Dominik Macháček, Mohammad Mahmoudi, Dario Franceschini, Ebrahim Ansari, Chiara Canton, Barry Haddow, Rishu Kumar, Philip Williams, Sebastian Stüker, Peter Polák, Rico Sennrich, Ivan Simonini, Felix Schneider, Alex Waibel, Sangeet Sagar, Otakar Smrž, Ondřej Bojar, Thai-Son Nguyen
Publikováno v:
EACL (System Demonstrations)
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
Proceedings of the 16th Conference of the European Chapter of the Association for Computational Linguistics: System Demonstrations
This paper presents an automatic speech translation system aimed at live subtitling of conference presentations. We describe the overall architecture and key processing components. More importantly, we explain our strategy for building a complex syst
Publikováno v:
EMNLP (Findings)
Zhang, B, Titov, I, Haddow, B & Sennrich, R 2020, Adaptive Feature Selection for End-to-End Speech Translation . in Findings of the Association for Computational Linguistics: EMNLP 2020 . pp. 2533-2544, The 2020 Conference on Empirical Methods in Natural Language Processing, Virtual conference, 16/11/20 . https://doi.org/10.18653/v1/2020.findings-emnlp.230
Findings of the Association for Computational Linguistics: EMNLP 2020
Zhang, B, Titov, I, Haddow, B & Sennrich, R 2020, Adaptive Feature Selection for End-to-End Speech Translation . in Findings of the Association for Computational Linguistics: EMNLP 2020 . pp. 2533-2544, The 2020 Conference on Empirical Methods in Natural Language Processing, Virtual conference, 16/11/20 . https://doi.org/10.18653/v1/2020.findings-emnlp.230
Findings of the Association for Computational Linguistics: EMNLP 2020
Information in speech signals is not evenly distributed, making it an additional challenge for end-to-end (E2E) speech translation (ST) to learn to focus on informative features. In this paper, we propose adaptive feature selection (AFS) for encoder-
Externí odkaz:
https://explore.openaire.eu/search/publication?articleId=doi_dedup___::925ac2a7b02df400f5f4f561cfb60673
https://www.zora.uzh.ch/id/eprint/191666/
https://www.zora.uzh.ch/id/eprint/191666/