MaskSound: Exploring Sound Masking Approaches to Support People with Autism in Managing Noise Sensitivity

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Park, A. Y., Jin, A., Huang, J. Z., Carr, J., & Jain, D. (2024). MaskSound: Exploring Sound Masking Approaches to Support People with Autism in Managing Noise Sensitivity. The 26th International ACM SIGACCESS Conference on Computers and Accessibility, 1-12. https://doi.org/10.1145/3663548.3675656

Publication date: 20 Oct 2024 Added to AutiHub: 21 Oct 2026 Type: Other Article language: English
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Authors

Publication authors
5
Publication authors identified as autistic
0 / 5 (0.0%)
  1. Anna Y Park
  2. Andy Jin
  3. Jeremy Zhengqi Huang
  4. Jesse Carr
  5. Dhruv Jain

Abstract

Noise sensitivity is a frequently reported characteristic in many autistic individuals. While strategies like sound isolation (e.g., noise-canceling headphones) and avoidance behaviors (e.g., leaving a crowded room) can help, they can reduce situational awareness and limit social engagement. In this paper, we examine an alternate approach to managing noise sensitivity: introducing ambient background sounds to reduce the perception of disruptive noises, i.e., sound masking. Through two studies (with ten and nine autistic individuals respectively), we investigated the autistic individuals’ preferred sound masks (e.g., white noise, brown noise, calming water sounds) for different contexts (e.g., traffic, speech) and elicited reactions for a future interactive tool to deliver effective sound masks. Our findings have implications not just for the accessibility community, but also for designers and researchers working on sound augmentation technology.

Bibliography cited by this reference

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Cited bibliography overview

These indicators describe the bibliography cited by this publication. An author name is counted each time it appears in one cited reference, so the same person can be counted more than once. Names not yet linked to an author already present in AutiHub are treated as unknown, not as non-autistic. Last computed: 23 Oct 2026 01:01.

Cited references
46
With a DOI
32
Without a DOI, from raw bibliography text
14
1 / 46 (2.2%) cited references include at least one author identified as autistic.
References with data to complete
7 / 46 (15.2%)
References with detected author names
39 / 46 (84.8%)
Without detected author names
7
Without a structured title
6
Without a stable identifier
13
References with raw author names still to review
7
References with external metadata lookup issues
0
These indicators apply to cited references displayed on this page, after technical duplicates have been merged. A reference without a DOI can still support author statistics when a title and author names are available.
Author names detected in the cited bibliography
162
From DOI or external metadata
162
From validated raw bibliography text
0
Raw names already validated
0
Raw names still to review
7
15 / 162 (9.3%) names are linked to an author already present in AutiHub. 147 / 162 (90.7%) names are not yet linked.
Names linked to a person identified as autistic
1 / 162 (0.6%)
Calculated across all author names detected in the cited bibliography. Among names linked to an author already present in AutiHub: 1 / 15 (6.7%). Distinct people identified as autistic: 1 / 154 (0.6%).
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