QuickQue: Enabling Quick Access to Information in User Reviews for Screen Reader Users

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.

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Publication Details

Published
2025-04-28
DOI
https://doi.org/10.1145/3744257.3744279
Citations
1
Primary Topic
Privacy-Preserving Technologies in Data
Type
article
Field-Weighted Citation Impact
2.48
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article

QuickQue: Enabling Quick Access to Information in User Reviews for Screen Reader Users

Akshay Kolgar Nayak, Mohan Sunkara, Yash Prakash, Vikas Ashok et al.
1 citations
Privacy-Preserving Technologies in Data
2.48
article

QuickQue: Enabling Quick Access to Information in User Reviews for Screen Reader Users

Akshay Kolgar Nayak, Mohan Sunkara, Yash Prakash, Vikas Ashok, Sampath Jayarathna, Hae-Na Lee, Sandeep Kalari
article en
1 citations

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.

Old Dominion University (US), Michigan State University (US)
Openalex Percentile: Top 8%
Privacy-Preserving Technologies in Data
2.48
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QuickQue: Enabling Quick Access to Information in User Reviews for Screen Reader Users — Akshay Kolgar Nayak, Mohan Sunkara, et al. · (2025) | TGRS Research Map | TGRS