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Effect of Occlusion on Deaf and Hard of Hearing Users’ Perception of Captioned Video Quality

Part of the Lecture Notes in Computer Science book series (LNISA,volume 12769)

Abstract

While the availability of captioned television programming has increased, the quality of this captioning is not always acceptable to Deaf and Hard of Hearing (DHH) viewers, especially for live or unscripted content broadcast from local television stations. Although some current caption metrics focus on textual accuracy (comparing caption text with an accurate transcription of what was spoken), other properties may affect DHH viewers’ judgments of caption quality. In fact, U.S. regulatory guidance on caption quality standards includes issues relating to how the placement of captions may occlude other video content. To this end, we conducted an empirical study with 29 DHH participants to investigate the effect on user’s judgements of caption quality or their enjoyment of the video, when captions overlap with an onscreen speaker’s eyes or mouth, or when captions overlap with onscreen text. We observed significantly more negative user-response scores in the case of such overlap. Understanding the relationship between these occlusion features and DHH viewers’ judgments of the quality of captioned video will inform future work towards the creation caption evaluation metrics, to help ensure the accessibility of captioned television or video.

Keywords

  • Occlusion
  • Stimuli
  • Caption
  • Metric

The contents of this paper were developed under a grant from the National Institute on Disability, Independent Living, and Rehabilitation Research (NIDILRR grant number #90DPCP0002). NIDILRR is a Center within the Administration for Community Living (ACL), Department of Health and Human Services (HHS). The contents of this paper do not necessarily represent the policy of NIDILRR, ACL, HHS, and you should not assume endorsement by the Federal Government.

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Notes

  1. 1.

    Throughout this paper, we use the term “metrics” to refer to some formula or algorithm that can produce a numerical score to represent the quality of a captioned video, whether it requires some human judgements or is calculated in a fully automatic manner. Thus, a metric may consider various features, and research on the relationship between features and the judgements of DHH viewers is foundational to deciding to incorporate particular features into a metric. Furthermore, we use the term “features” to refer to the aspects or properties of captioned video that may contribute to its quality. For instance, some prior research has investigated how DHH individuals’ judgements of the quality of captions may be influenced by: incorrect transcription of speech into text [32], the latency of the caption relative to the timing of speech [33], font size or color in captions [5, 7], and other features.

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Amin, A.A., Hassan, S., Huenerfauth, M. (2021). Effect of Occlusion on Deaf and Hard of Hearing Users’ Perception of Captioned Video Quality. In: Antona, M., Stephanidis, C. (eds) Universal Access in Human-Computer Interaction. Access to Media, Learning and Assistive Environments. HCII 2021. Lecture Notes in Computer Science(), vol 12769. Springer, Cham. https://doi.org/10.1007/978-3-030-78095-1_16

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