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Automated Interactive Video Playback for Studies of Animal Communication

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ViDscribe: Multimodal AI for Customizing Audio Description and Question Answering in Online Videos.

Maryam S Cheema¹, Pooyan Fazli¹, Sina Elahimanesh²

¹Arizona State University Tempe, Arizona, USA.

Extended Abstracts on Human Factors in Computing Systems. CHI Conference

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Summary

ViDscribe offers personalized audio descriptions (ADs) and conversational question answering for YouTube videos. Customized ADs and interactive features enhance video accessibility and engagement for blind and low vision (BLV) users.

Keywords:

Audio Description Blind and Low Vision Users Customization Longitudinal Study Multimodal Large Language Models Video Accessibility Visual Question Answering

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Published on: December 23, 2025

Area of Science:

Artificial Intelligence
Human-Computer Interaction
Accessibility Technology

Background:

Multimodal large language models advance automatic video narration and question answering (VQA).
Existing AI-driven audio description (AD) systems lack personalization for diverse user needs and are evaluated in limited settings.
Scalable alternatives to human-authored ADs are needed for blind and low vision (BLV) viewers.

Purpose of the Study:

To introduce ViDscribe, a web-based platform for AI-generated ADs with user customization and VQA.
To evaluate the longitudinal engagement and impact of ViDscribe's features in real-world settings.
To assess the effectiveness of personalized, interactive video access for BLV users.

Main Methods:

Developed ViDscribe, integrating AI-generated ADs, six customization types, and a conversational VQA interface for YouTube.
Conducted a longitudinal, in-the-wild study with eight BLV participants.
Analyzed user engagement with customization and VQA features over time.

Main Results:

Participants showed sustained engagement with both customization and VQA features.
Customized ADs led to improvements in effectiveness, enjoyment, and immersion compared to default ADs.
The study demonstrated the value of personalized and interactive video access.

Conclusions:

ViDscribe's personalized and interactive approach significantly enhances video accessibility for BLV individuals.
User engagement and satisfaction are improved through tailored ADs and conversational VQA.
Future systems should prioritize adaptive and customizable features for inclusive digital content consumption.