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Describe Now: User-Driven Audio Description for Blind and Low Vision Individuals
Maryam Cheema1, Hasti Seifi1, Pooyan Fazli1
1Arizona State University Tempe, Arizona, USA.
This study introduces user-controlled, AI-generated audio descriptions (AD) for blind and low vision (BLV) users, offering customizable content and timing. Findings highlight preferences for AD detail and delivery, informing future accessibility tools.
Area of Science:
- Human-Computer Interaction
- Accessibility Technology
- Assistive Technology
Background:
- Audio descriptions (AD) enhance video accessibility for blind and low vision (BLV) users by describing visual content.
- Current AD methods are time-consuming and lack viewer control over content, timing, and detail.
Purpose of the Study:
- To explore user-driven, AI-generated audio descriptions for BLV users.
- To enable BLV viewers to control the timing and detail level of ADs.
Main Methods:
- A study involving 20 BLV participants.
- Participants used AI-generated ADs with concise and detailed options across seven video genres.
- Evaluation of user control, preferences, and limitations.
Main Results:
- Significant differences in preferred AD frequency and detail across video genres were observed.
- Participants reported a greater sense of control with user-driven AD delivery.
- Identified limitations in the current AI-generated AD system.
Conclusions:
- User-driven AI-generated ADs offer enhanced control and customization for BLV users.
- Findings provide crucial insights for developing next-generation AD tools.
- Future AD systems should prioritize user agency and adaptive content delivery.
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