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
Parents
14
Improving Real-Time Captioning Experiences for Deaf and Hard of Hearing Students
Saba Kawas, George Karalis, Tzu Wen et al. · 2016 · 80 citations
A Survey on Different Types of CAPTCHA
Pavan Kumar Kulluru, Taslim Shaikh, Shreepad Bidwai et al. · 2016 · 58 citations
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University of Washington
Seattle, United States
2 h-index
11 publications
509 citations
Carnegie Mellon University
Pittsburgh, United States
2 h-index
1 publications
22 citations
Jiangxi College of Applied Technology
Ganzhou, China
1 h-index
1 publications
28 citations
Syracuse University
Syracuse, United States
1 h-index
3 publications
66 citations

Tel Aviv University
Tel Aviv, Israel
1 h-index
1 publications
23 citations

University of Rochester
Rochester, United States
1 h-index
3 publications
189 citations
Allen Institute
Seattle, United States
1 h-index
7 publications
189 citations

The University of Adelaide
Adelaide, Australia
1 h-index
1 publications
19 citations
1–8 of 20
Conference · 2 publications · 69 citations
2
h-index
Repository · 1 publications · 88 citations
1
h-index
ARCME · 1 publications · 48 citations
1
h-index
1 publications · 11 citations
1
h-index
1 publications · 23 citations
1
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1–5