Few VR applications and games implement captioning of speech and audio cues, which either inhibits or prevents access of their application by deaf or hard of hearing (DHH) users, new language learners, and other caption users. Additionally, little to no guidelines exist on how to implement live captioning on VR headsets and how it may differ from traditional television captioning. To help fill the void of information behind user preferences of different VR captioning styles, we conducted a study with eight DHH participants to test three caption movement behaviors (head-locked, lag, and appear- locked) while watching live-captioned, single-speaker presentations in VR. Participants answered a series of Likert scale and open-ended questions about their experience. Participants’ preferences were split, but most participants reported feeling comfortable with using live captions in VR and enjoyed the experience. When participants ranked the caption behaviors, there was almost an equal divide between the three types tested. IPQ results indicated each behavior had similar immersion ratings, however participants found head-locked and lag captions more user-friendly than appear-locked captions. We suggest that participants may vary in caption preference depending on how they use captions, and that providing opportunities for caption customization is best.
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Exploring the Design Space of Automatically Generated Emotive Captions for Deaf or Hard of Hearing Users
Caption text conveys salient auditory information to deaf or hard-of-hearing (DHH) viewers. However, the emotional information within the speech is not captured. We developed three emotive captioning schemas that map the output of audio-based emotion detection models to expressive caption text that can convey underlying emotions. The three schemas used typographic changes to the text, color changes, or both. Next, we designed a Unity framework to implement these schemas and used it to generate stimuli videos. In an experimental evaluation with 28 DHH viewers, we compared DHH viewers’ ability to understand emotions and their subjective judgments across the three captioning schemas. We found no significant difference in participants’ ability to understand the emotion based on the captions or their subjective preference ratings. Open-ended feedback revealed factors contributing to individual differences in preferences among the participants and challenges with automatically generated emotive captions that motivate future work.
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- PAR ID:
- 10442631
- Date Published:
- Journal Name:
- Extended Abstracts of the 2023 CHI Conference on Human Factors in Computing Systems (CHI EA '23)
- Page Range / eLocation ID:
- 1 to 10
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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Few VR applications and games implement captioning of speech and audio cues, which either inhibits or prevents access of their application by deaf or hard of hearing (DHH) users, new language learners, and other caption users. Additionally, little to no guidelines exist on how to implement live captioning on VR headsets and how it may differ from traditional television captioning. To help fill the void of information behind user preferences of different VR captioning styles, we conducted a study with eight DHH participants to test three caption movement behaviors (head-locked, lag, and appearlocked) while watching live-captioned, single-speaker presentations in VR. Participants answered a series of Likert scale and open-ended questions about their experience. Participants’ preferences were split, but most participants reported feeling comfortable with using live captions in VR and enjoyed the experience. When participants ranked the caption behaviors, there was almost an equal divide between the three types tested. IPQ results indicated each behavior had similar immersion ratings, however participants found head-locked and lag captions more user-friendly than appear-locked captions. We suggest that participants may vary in caption preference depending on how they use captions, and that providing opportunities for caption customization is bestmore » « less
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Affective captions employ visual typographic modulations to convey a speaker’s emotions, improving speech accessibility for Deaf and Hard-of-Hearing (dhh) individuals. However, the most effective visual modulations for expressing emotions remain uncertain. Bridging this gap, we ran three studies with 39 dhh participants, exploring the design space of affective captions, which include parameters like text color, boldness, size, and so on. Study 1 assessed preferences for nine of these styles, each conveying either valence or arousal separately. Study 2 combined Study 1’s top-performing styles and measured preferences for captions depicting both valence and arousal simultaneously. Participants outlined readability, minimal distraction, intuitiveness, and emotional clarity as key factors behind their choices. In Study 3, these factors and an emotion-recognition task were used to compare how Study 2’s winning styles performed versus a non-styled baseline. Based on our findings, we present the two best-performing styles as design recommendations for applications employing affective captions.more » « less
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null (Ed.)Deaf and hard of hearing (DHH) viewers watch multimedia with captions on devices with widely varying widths. We investigated the impact of caption width on viewers' preferences. Previous research has shown that presenting one word lines allows viewers to read much more quickly than traditional reading, while others have shown that the optimal width for captions is 6 words per line. Our study showed that DHH viewers had no preference difference between 6 and 12 word lines. Furthermore, they significantly preferred 6 and 12 word lines over single word lines due to the need to split attention between the captions and video.more » « less
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Evaluating the quality of accessible image captions with human raters is difficult, as it may be difficult for a visually impaired user to know how comprehensive a caption is, whereas a sighted assistant may not know what information a user will need from a caption. To explore how image captioners and caption consumers assess caption content, we conducted a series of collaborative captioning sessions in which six pairs, consisting of a blind person and their sighted partner, worked together to discuss, create, and evaluate image captions. By making captioning a collaborative task, we were able to observe captioning strategies, to elicit questions and answers about image captions, and to explore blind users’ caption preferences. Our findings provide insight about the process of creating good captions and serve as a case study for cross-ability collaboration between blind and sighted people.more » « less
- Free Publicly Accessible Full Text
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Accepted Manuscript1.0
- Conference Paper:
- https://doi.org/10.1145/3544549.3585880
