Cross-linguistic Adaptation

Cross-Linguistic Adaptation is a methodological framework in computational linguistics that enables the transfer and adaptation of linguistic knowledge, models, or resources from one language to another to improve performance in low-resource languages.

90

Publications

3.6K

Citations

326

Authors

131

Institutions

Publications per year

2017–2026

35

Authors

326

  1. TS
    Tanja Schultz

    Carnegie Mellon University, United States

    4 publications · 183 citations

    4

    h-index

  2. MB
    Mara Behlau

    Centro de Estudos da Voz, Brazil

    3 publications · 51 citations

    3

    h-index

  3. SK
    Sanjeev Khudanpur

    Johns Hopkins University, United States

    3 publications · 60 citations

    3

    h-index

  4. NT
    Ngoc Thang Vu

    University of Stuttgart, Germany

    3 publications · 123 citations

    3

    h-index

  5. PF
    Pascale Fung

    Hong Kong University of Science and Technology, Hong Kong SAR China

    2 publications · 33 citations

    2

    h-index

1–5 of 326

Venues

  1. PubMed

    Repository · 4 publications · 195 citations

    4

    h-index

  2. CoDAS

    4 publications · 71 citations

    4

    h-index

  3. arXiv (Cornell University)

    Repository · 3 publications · 61 citations

    3

    h-index

  4. Figshare

    Repository · 2 publications · 87 citations

    2

    h-index

  5. Annals of Indian Academy of Neurology

    AIAN · 2 publications · 45 citations

    2

    h-index

1–5