Survey of Low-Resource Machine Translation

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 translation models. There has been increasing interest in...

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Vydáno v:Computational linguistics - Association for Computational Linguistics Ročník 48; číslo 3; s. 673 - 732
Hlavní autoři: Haddow, Barry, Bawden, Rachel, Barone, Antonio Valerio Miceli, Helcl, Jindřich, Birch, Alexandra
Médium: Journal Article
Jazyk:angličtina
Vydáno: One Broadway, 12th Floor, Cambridge, Massachusetts 02142, USA MIT Press 01.09.2022
MIT Press Journals, The
Massachusetts Institute of Technology Press (MIT Press)
The MIT Press
Témata:
Computation and Language
Computer Science
Languages
Machine translation
Polls & surveys
Training
Translation
ISSN:0891-2017, 1530-9312
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Abstract 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 translation models. There has been increasing interest in research addressing the challenge of producing useful translation models when very little translated training data is available. We present a summary of this topical research field and provide a description of the techniques evaluated by researchers in several recent shared tasks in low-resource MT.
AbstractList 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 translation models. There has been increasing interest in research addressing the challenge of producing useful translation models when very little translated training data is available. We present a summary of this topical research field and provide a description of the techniques evaluated by researchers in several recent shared tasks in low-resource MT.
Author Bawden, Rachel
Haddow, Barry
Birch, Alexandra
Barone, Antonio Valerio Miceli
Helcl, Jindřich
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  givenname: Rachel
  surname: Bawden
  fullname: Bawden, Rachel
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  organization: Inria, France. Rachel.bawden@inria.fr
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  givenname: Antonio Valerio Miceli
  surname: Barone
  fullname: Barone, Antonio Valerio Miceli
  organization: University of Edinburgh School of Informatics. amiceli@ed.ac.uk
– sequence: 4
  givenname: Jindřich
  surname: Helcl
  fullname: Helcl, Jindřich
  email: jhelcl@ed.ac.uk
  organization: University of Edinburgh School of Informatics. jhelcl@ed.ac.uk
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  givenname: Alexandra
  surname: Birch
  fullname: Birch, Alexandra
  email: a.birch@ed.ac.uk
  organization: University of Edinburgh School of Informatics .a.birch@ed.ac.uk
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Snippet 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...
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SubjectTerms Computation and Language
Computer Science
Languages
Machine translation
Polls & surveys
Training
Translation
Title Survey of Low-Resource Machine Translation
URI https://direct.mit.edu/coli/article/doi/10.1162/coli_a_00446
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