CaptionCrowd is an interactive platform developed within the IKILeUS project at the University of Stuttgart to improve video caption accuracy for the Deaf and Hard of Hearing (DHH) community. While automatic captions provide some accessibility, they often contain errors in grammar, homophones, and domain-specific terminology, making comprehension challenging. CaptionCrowd enables users to collaboratively identify and correct inaccurate captions in real-time, improving their quality through community-driven feedback.The platform features a user-friendly web-based video player that allows users to highlight incorrect words in subtitles, with their selections recorded for further analysis. User testing with 16 participants revealed that manually correcting captions can be cognitively demanding, highlighting the ongoing need for enhanced accessibility solutions.
%0 Generic
%1 fathallah2025caption
%A Fathallah, Nadeen
%A Staab, Steffen
%D 2025
%K darus ubs_10005 ubs_20008 ubs_30223 ubs_40506 unibibliografie
%R 10.18419/darus-4775
%T Code for Caption Crowd (IKILeUS) : A Collaborative Platform for Improving Automated Captions Through User Feedback
%X CaptionCrowd is an interactive platform developed within the IKILeUS project at the University of Stuttgart to improve video caption accuracy for the Deaf and Hard of Hearing (DHH) community. While automatic captions provide some accessibility, they often contain errors in grammar, homophones, and domain-specific terminology, making comprehension challenging. CaptionCrowd enables users to collaboratively identify and correct inaccurate captions in real-time, improving their quality through community-driven feedback.The platform features a user-friendly web-based video player that allows users to highlight incorrect words in subtitles, with their selections recorded for further analysis. User testing with 16 participants revealed that manually correcting captions can be cognitively demanding, highlighting the ongoing need for enhanced accessibility solutions.
@misc{fathallah2025caption,
abstract = {CaptionCrowd is an interactive platform developed within the IKILeUS project at the University of Stuttgart to improve video caption accuracy for the Deaf and Hard of Hearing (DHH) community. While automatic captions provide some accessibility, they often contain errors in grammar, homophones, and domain-specific terminology, making comprehension challenging. CaptionCrowd enables users to collaboratively identify and correct inaccurate captions in real-time, improving their quality through community-driven feedback.The platform features a user-friendly web-based video player that allows users to highlight incorrect words in subtitles, with their selections recorded for further analysis. User testing with 16 participants revealed that manually correcting captions can be cognitively demanding, highlighting the ongoing need for enhanced accessibility solutions. },
added-at = {2025-03-03T09:44:34.000+0100},
affiliation = {Fathallah, Nadeen/University of Stuttgart, Staab, Steffen/University of Stuttgart},
author = {Fathallah, Nadeen and Staab, Steffen},
biburl = {https://puma.ub.uni-stuttgart.de/bibtex/299bf50e2ba8093aeac214f29e0bd12c3/unibiblio},
doi = {10.18419/darus-4775},
howpublished = {Software},
interhash = {6a7c879a80258c47936352b963b2ffe9},
intrahash = {99bf50e2ba8093aeac214f29e0bd12c3},
keywords = {darus ubs_10005 ubs_20008 ubs_30223 ubs_40506 unibibliografie},
orcid-numbers = {Fathallah, Nadeen/https://orcid.org/0000-0001-7921-034X, Staab, Steffen/https://orcid.org/0000-0002-0780-4154},
timestamp = {2025-03-03T09:44:34.000+0100},
title = {Code for Caption Crowd (IKILeUS) : A Collaborative Platform for Improving Automated Captions Through User Feedback},
year = 2025
}
