Word-based Machine Translation

Word-Based Machine Translation is a machine translation approach that operates by aligning and translating individual words between source and target languages without significant consideration of contextual or syntactic structures.

186

Publications

13K

Citations

529

Authors

148

Institutions

Publications per year

2017–2026

45

Authors

529

  1. PK
    Philipp Koehn

    University of Edinburgh, United Kingdom

    13 publications · 5.3K citations

    13

    h-index

  2. HN
    Hermann Ney

    RWTH Aachen University, Germany

    9 publications · 522 citations

    9

    h-index

  3. AW
    Alex Waibel

    Carnegie Mellon University, United States

    8 publications · 268 citations

    8

    h-index

  4. OB
    Ondřej Bojar

    Charles University, Czechia

    8 publications · 1.6K citations

    8

    h-index

  5. BH
    Barry Haddow

    University of Edinburgh, United Kingdom

    6 publications · 1.6K citations

    6

    h-index

1–5 of 529

Venues

  1. arXiv (Cornell University)

    Repository · 8 publications · 342 citations

    8

    h-index

  2. Edinburgh Research Explorer (University of Edinburgh)

    Repository · 5 publications · 912 citations

    5

    h-index

  3. Arrow@dit (Dublin Institute of Technology)

    Repository · 3 publications · 80 citations

    3

    h-index

  4. Neural Computing and Applications

    3 publications · 69 citations

    3

    h-index

  5. Computational Linguistics

    3 publications · 137 citations

    3

    h-index

1–5