Deaf and hard-of-hearing users' prioritization of genres of online video content requiring accurate captions-Reference-Cited by-同舟云学术

Deaf and hard-of-hearing users' prioritization of genres of online video content requiring accurate captions

Published:2020-04-17 Issue: Volume: Page:
ISSN:
Container-title:Proceedings of the 17th International Web for All Conference
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Author:

Berke Larwan¹,Seita Matthew¹,Huenerfauth Matt¹

Affiliation:

1. Rochester Institute of Technology

Funder

Microsoft Research

U.S. Department of Health and Human Services

Microsoft

National Science Foundation

Publisher

ACM

Link

https://dl.acm.org/doi/pdf/10.1145/3371300.3383337

Reference59 articles.

1. Using Miscue Analysis to Assess Comprehension in Deaf College Readers

2. Jon P. Barker Ricard Marxer Emmanuel Vincent Shinji Watanabe. 2017. The CHiME challenges: Robust speech recognition in everyday environments. In: Watanabe S. Delcroix M. Metze F. Hershey J. (eds.) New Era for Robust Speech Recognition. Springer Cham 327--344. 10.1007/978-3-319-64680-0_14 Jon P. Barker Ricard Marxer Emmanuel Vincent Shinji Watanabe. 2017. The CHiME challenges: Robust speech recognition in everyday environments. In: Watanabe S. Delcroix M. Metze F. Hershey J. (eds.) New Era for Robust Speech Recognition. Springer Cham 327--344. 10.1007/978-3-319-64680-0_14

3. Deaf and Hard-of-Hearing Perspectives on Imperfect Automatic Speech Recognition for Captioning One-on-One Meetings

4. Juan Cao Yong-Dong Zhang Yi-Cheng Song Zhi-Neng Chen Xu Zhang and Jin-Tao Li. 2009. MCG-WEBV: A benchmark dataset for web video analysis. Beijing:Institute of Computing Technology 10 (2009) 324--334. Juan Cao Yong-Dong Zhang Yi-Cheng Song Zhi-Neng Chen Xu Zhang and Jin-Tao Li. 2009. MCG-WEBV: A benchmark dataset for web video analysis. Beijing:Institute of Computing Technology 10 (2009) 324--334.

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