Document Type

Conference Paper

Publication Date

2026

DOI

10.1145/3786304.3788850

Publication Title

CHIIR '26: Proceedings of the 2026 Conference on Human Information Interaction and Retrieval

Pages

285-294

Conference Name

CHIIR '26: 2026 ACM SIGIR Conference on Human Information Interaction and Retrieval, March 22-26, 2026, Seattle USA

Abstract

Online discussions have become integral to how people exchange ideas, form opinions, and participate in collective deliberation. While sighted users can comfortably engage with online discussions, blind users who are dependent on screen readers are forced to listen to long threads narrated in a single, monotonic voice that lacks prosodic variation, rhythm, or emotion. This robotic auditory experience not only deteriorates the user engagement with the content but also increases cognitive strain, by making it difficult to remain attentive and discern meaning beyond literal words. In an interview study, most blind participants reported that monotonous narration hindered their ability to detect salient information, perceive emotional cues, and comprehend content authors’ intents in discussions. Many described experiencing mental fatigue when listening to ‘flat’, ‘uninspiring’ voices, noting that their attention tended to diminish quickly over time. The participants also indicated that they often tried to ‘add’ prosodic variation or emotional inflection themselves in their minds, but characterized this compensatory effort as mentally taxing and cognitively demanding. To address this issue, we introduce VoxVista, a multi-voice design framework driven by a large language model that leverages a custom voice-preference dataset to assign personalized voice profiles to user posts in discussions, thereby replacing the traditional monotone narration in screen readers with a more expressive, dynamic, and contextually-aware narration. In a study with 20 blind participants, we observed that VoxVista significantly improved user engagement, comprehension, and willingness to continue listening to longer discussions.

Rights

© 2026 Copyright held by the owner/authors.

This work is licensed under a Creative Commons Attribution 4.0 International License.

Original Publication Citation

Prakash, Y., Nayak, A. K., Alyaan, M. S., Jayarathna, S., Lee, H.-N., & Ashok, V. (2026). VoxVista: Enhancing screen reading experience for online user comments. In C. Shah, R. W. White, A. Fourney, C. T. Lopes, & J. Trippas (Eds), CHIIR '26: Proceedings of the 2026 Conference on Human Information Interaction and Retrieval (pp. 285-294). Association for Computing Machinery. https://doi.org/10.1145/3786304.3788850

ORCID

0000-0001-8593-327X (Prakash), 0009-0000-9992-9706 (Nayak), 0009-0002-7353-4698 (Alyaan), 0000-0002-4879-7309 (Jayarathna), 0000-0002-4772-1265 (Ashok)

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