Machine-assisted Captioning

Machine-Assisted Captioning is a subtitling methodology that integrates automated speech recognition and natural language processing technologies to support human editors in generating accurate, synchronized text for the deaf or hard-of-hearing, thereby enhancing efficiency and consistency in the production of subtitles within the domain of SDH (Subtitles for the Deaf and Hard of Hearing).

14

Publications

534

Citations

50

Authors

20

Institutions

Publications per year

2017–2026

10

Authors

50

  1. JP
    Jeffrey P. Bigham

    Carnegie Mellon University, United States

    2 publications · 85 citations

    2

    h-index

  2. XC
    Xi Chen

    Google (United States), United States

    1 publications · 42 citations

    1

    h-index

  3. KS
    Keisuke Sakaguchi

    Johns Hopkins University, United States

    1 publications · 27 citations

    1

    h-index

  4. AT
    Aris T. Papageorghiou

    University of Oxford, United Kingdom

    1 publications · 23 citations

    1

    h-index

  5. RS
    Radu Soricut

    Google (United States), United States

    1 publications · 42 citations

    1

    h-index

1–5 of 50

Venues

  1. 2

    h-index

  2. arXiv (Cornell University)

    Repository · 1 publications · 88 citations

    1

    h-index

  3. Archives of Computational Methods in Engineering

    ARCME · 1 publications · 48 citations

    1

    h-index

  4. 1

    h-index

  5. Medical Image Analysis

    1 publications · 23 citations

    1

    h-index

1–5