Evaluating Quality and Comprehension of Real-Time Sign Language Video on Mobile Phones
Jessica J. Tran, Joy Kim, Jaehong Chon, Eve A. Riskin, Richard E. Ladner and Jacob O. WobbrockAbstract
Video and image quality are often objectively measured using peak signal-to-noise ratio (PSNR), but for sign language video, human comprehension is most important. In this study, we determine how well the objective PSNR metric matches human comprehension of sign language video. For the study, we use very low bitrates (10-60 kbps) and several low spatial resolutions (192×144 and 320×240 pixels) which may be typical of video transmission on mobile phones using 3G networks. In a national online video-equipped user survey of 103 respondents, we found that respondents preferred the 320×240 spatial resolution transmitted at 20 kbps and higher which does not match what PSNR results would predict. However, when comparing ease/difficulty of comprehension, we found that responses did correlate with measured PSNR. This suggests that PSNR may not be suitable for representing subjective video quality, but can be reliable as a measure for comprehensibility of American Sign Language (ASL) video. These findings are applied to our experimental mobile phone application, MobileASL, which enables real-time sign language communication for Deaf users at low bandwidths over the U.S. 3G cellular network.Back to List of Accepted Papers