Year: 2025
Type: conference-paper
Abstract: Efficiently perusing online customer reviews is presently challenging for blind users, who rely on a screen reader that supports predominantly one-dimensional narration of content via keyboard shortcuts.To address this, with restaurant reviews as seminal case study, we developed QuickCue, a browser extension prototype that enables screen reader users to quickly obtain the positives and negatives regarding different aspects of a restaurant (e.g., food quality, hygiene, ambiance), without having to sift through numerous reviews containing redundant information.At its core, QuickCue utilizes a large language model to perform aspect and sentiment-based joint classification of reviews to group them based on the types of contained information, followed by focused summarizations within the groups to generate concise representations of reviewers' opinions, which are then presented to users via an accessible interface.Evaluation of QuickCue in a user study with 10 participants showed significant improvements in overall usability and task workload compared to the status quo screen reader.
Institutions: Old Dominion University, Michigan State University
Language: English
Subfield: Human Factors and Ergonomics
Field: Social Sciences
Domain: Social Sciences
Open Access status: hybrid
OpenAlex ID: W4415208104