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It's All About the Message: Visual Experience is a Precursor to Accurate Auditory Interaction

Published: 13 May 2019 Publication History

Abstract

Anecdotal evidence suggests there is a disjoint between the interaction experiences of sighted and visually disabled web users. However, we propose the converse and suggest that this disjoint is created by the lack of understanding of the interplay between the two domains. Current research shows that there is one single locus of attention at a given time in the context of web interaction, and therefore sighted users form a serialisation of the things they look at and pay attention - an exemplar of which can be seen in eye movement sequences of users. We also suggest that web designers have a narrative in mind to be experienced by users, and they create a visual sequence they wish their audience to perceive for supporting this narrative. However, this sequence is typically lost when we move from visual presentations to auditory ones. Current audio interactions centre around page linearisation based on the sequence of the underlying source code. This linearisation typically falls short of the kind of comprehensive interaction which can be expected in the visual domain. In this paper, we use an eye tracking dataset to illustrate that the linearisation of web page component based on the underlying source code differs from what is experienced by sighted users. We then show that the web experience of visually disabled users can be improved by re-ordering the most commonly used web page components based on the order in which they are used. We also suggest that it is critical to conduct formative experimentation with sighted users to establish a visual narrative and serialisation, thereby informing the design of the auditory conversation.

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Cited By

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  • (2023)Predicting Trending Elements on Web Pages Using Machine LearningInternational Journal of Human–Computer Interaction10.1080/10447318.2023.226167740:22(7065-7080)Online publication date: 2-Oct-2023
  • (2022)Framework for experiential transcoding of web pages with scanpath trend analysisProceedings of the 19th International Web for All Conference10.1145/3493612.3520450(1-5)Online publication date: 25-Apr-2022
  • (2020)Eye-tracking scanpath trend analysis for autism detectionACM SIGACCESS Accessibility and Computing10.1145/3441497.3441498(1-8)Online publication date: 4-Dec-2020
  • Show More Cited By

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cover image ACM Other conferences
W4A '19: Proceedings of the 16th International Web for All Conference
May 2019
224 pages
ISBN:9781450367165
DOI:10.1145/3315002
Permission to make digital or hard copies of all or part of this work for personal or classroom use is granted without fee provided that copies are not made or distributed for profit or commercial advantage and that copies bear this notice and the full citation on the first page. Copyrights for components of this work owned by others than ACM must be honored. Abstracting with credit is permitted. To copy otherwise, or republish, to post on servers or to redistribute to lists, requires prior specific permission and/or a fee. Request permissions from [email protected]

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Publication History

Published: 13 May 2019

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Author Tags

  1. Eye Tracking
  2. STA; Experiential Transcoding
  3. Scanpath Trend Analysis
  4. Visual Elements
  5. Web Pages

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  • Refereed limited

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W4A '19

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W4A '19 Paper Acceptance Rate 18 of 49 submissions, 37%;
Overall Acceptance Rate 171 of 371 submissions, 46%

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Cited By

View all
  • (2023)Predicting Trending Elements on Web Pages Using Machine LearningInternational Journal of Human–Computer Interaction10.1080/10447318.2023.226167740:22(7065-7080)Online publication date: 2-Oct-2023
  • (2022)Framework for experiential transcoding of web pages with scanpath trend analysisProceedings of the 19th International Web for All Conference10.1145/3493612.3520450(1-5)Online publication date: 25-Apr-2022
  • (2020)Eye-tracking scanpath trend analysis for autism detectionACM SIGACCESS Accessibility and Computing10.1145/3441497.3441498(1-8)Online publication date: 4-Dec-2020
  • (2020)Autism detection based on eye movement sequences on the webProceedings of the 17th International Web for All Conference10.1145/3371300.3383340(1-10)Online publication date: 20-Apr-2020

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