A readability evaluation of real-time crowd captions in the classroom

  • Authors:

  • Raja S. Kushalnagar;Walter S. Lasecki;Jeffrey P. Bigham

  • Affiliations:

  • Rochester Institute of Technology, Rochester, NY, USA;University of Rochester, Rochester, NY, USA;University of Rochester, Rochester, NY, USA

  • Venue:
  • Proceedings of the 14th international ACM SIGACCESS conference on Computers and accessibility
  • Year:
  • 2012

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Abstract

Deaf and hard of hearing individuals need accommodations that transform aural to visual information, such as captions that are generated in real-time to enhance their access to spoken information in lectures and other live events. The captions produced by professional captionists work well in general events such as community or legal meetings, but is often unsatisfactory in specialized content events such as higher education classrooms. In addition, it is hard to hire professional captionists, especially those that have experience in specialized content areas, as they are scarce and expensive. The captions produced by commercial automatic speech recognition (ASR) software are far cheaper, but is often perceived as unreadable due to ASR's sensitivity to accents, background noise and slow response time. We ran a study to evaluate the readability of captions generated by a new crowd captioning approach versus professional captionists and ASR. In this approach, captions are typed by classmates into a system that aligns and merges the multiple incomplete caption streams into a single, comprehensive real-time transcript. Our study asked 48 deaf and hearing readers to evaluate transcripts produced by a professional captionist, ASR and crowd captioning software respectively and found the readers preferred crowd captions over professional captions and ASR.