Uncovering patterns in reviewers’ feedback to scene description authors

Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer fee...

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Main Authors: NATALIE, Rosiana, LOH, Jolene Kar Inn, TAN, Huei Suen, TSENG, Joshua Shi-hao, HARA, Kotaro
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Language:English
Published: Institutional Knowledge at Singapore Management University 2021
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Online Access:https://ink.library.smu.edu.sg/sis_research/6751
https://ink.library.smu.edu.sg/context/sis_research/article/7754/viewcontent/3441852.3476550.pdf
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spelling sg-smu-ink.sis_research-77542022-01-27T10:45:48Z Uncovering patterns in reviewers’ feedback to scene description authors NATALIE, Rosiana LOH, Jolene Kar Inn TAN, Huei Suen TSENG, Joshua Shi-hao HARA, Kotaro Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1,120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or speech action that the reviewers used, (iii) Required Action; the recommended action that the authors should do to improve the AD, and (iv) Guidance; the additional help that the reviewers gave to help the authors. We discuss which of these patterns could be automated within the review process as design implications for future AD collaborative authoring systems. 2021-10-01T07:00:00Z text application/pdf https://ink.library.smu.edu.sg/sis_research/6751 info:doi/10.1145/3441852.3476550 https://ink.library.smu.edu.sg/context/sis_research/article/7754/viewcontent/3441852.3476550.pdf http://creativecommons.org/licenses/by-nc-nd/4.0/ Research Collection School Of Computing and Information Systems eng Institutional Knowledge at Singapore Management University Audio Description visual impairment video accessibility collaborative writing Graphics and Human Computer Interfaces
institution Singapore Management University
building SMU Libraries
continent Asia
country Singapore
Singapore
content_provider SMU Libraries
collection InK@SMU
language English
topic Audio Description
visual impairment
video accessibility
collaborative writing
Graphics and Human Computer Interfaces
spellingShingle Audio Description
visual impairment
video accessibility
collaborative writing
Graphics and Human Computer Interfaces
NATALIE, Rosiana
LOH, Jolene Kar Inn
TAN, Huei Suen
TSENG, Joshua Shi-hao
HARA, Kotaro
Uncovering patterns in reviewers’ feedback to scene description authors
description Audio descriptions (ADs) can increase access to videos for blind people. Researchers have explored different mechanisms for generating ADs, with some of the most recent studies involving paid novices; to improve the quality of their ADs, novices receive feedback from reviewers. However, reviewer feedback is not instantaneous. To explore the potential for real-time feedback through automation, in this paper, we analyze 1,120 comments that 40 sighted novices received from a sighted or a blind reviewer. We find that feedback patterns tend to fall under four themes: (i) Quality; commenting on different AD quality variables, (ii) Speech Act; the utterance or speech action that the reviewers used, (iii) Required Action; the recommended action that the authors should do to improve the AD, and (iv) Guidance; the additional help that the reviewers gave to help the authors. We discuss which of these patterns could be automated within the review process as design implications for future AD collaborative authoring systems.
format text
author NATALIE, Rosiana
LOH, Jolene Kar Inn
TAN, Huei Suen
TSENG, Joshua Shi-hao
HARA, Kotaro
author_facet NATALIE, Rosiana
LOH, Jolene Kar Inn
TAN, Huei Suen
TSENG, Joshua Shi-hao
HARA, Kotaro
author_sort NATALIE, Rosiana
title Uncovering patterns in reviewers’ feedback to scene description authors
title_short Uncovering patterns in reviewers’ feedback to scene description authors
title_full Uncovering patterns in reviewers’ feedback to scene description authors
title_fullStr Uncovering patterns in reviewers’ feedback to scene description authors
title_full_unstemmed Uncovering patterns in reviewers’ feedback to scene description authors
title_sort uncovering patterns in reviewers’ feedback to scene description authors
publisher Institutional Knowledge at Singapore Management University
publishDate 2021
url https://ink.library.smu.edu.sg/sis_research/6751
https://ink.library.smu.edu.sg/context/sis_research/article/7754/viewcontent/3441852.3476550.pdf
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