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Unblind the charts: Towards Making Interactive Charts Accessible in Android Applications

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arxiv 2109.12442 v1 pith:MU66DQ6D submitted 2021-09-25 cs.HC cs.SE

classification cs.HCcs.SE
keywords accessibilitychartsandroidapplicationschartdevelopersimpairedsmartphones
verification ladder T0 review T1 audit T2 compute T3 formal
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Smartphones are a crucial aspect of routine life in the modern world, and viewing information graphics such as charts becomes common practice for many unassuming tasks. However, for the vision impaired, accessing graphical material presents many difficulties. Android smartphones usually come preinstalled with Google Talkback as a default screen-reader, which attempts to cater for the visually impaired by providing supplementary auditory information when interfacing with supported applications. Still, the crux of this situation is that screen-readers rely on developers correctly implementing the required accessibility guidelines for UI elements, such as charts. Unfortunately, according to the empirical study, more than 88% of the charts found in real-world Android applications are inaccessible to a vision-impaired user, contributing to the wider accessibility issues faced by vision impaired users of smartphones. These accessibility issues can be attributed to a knowledge gap in considering possible disabilities for users, and time costs for developers. To overcome these challenges, this study proposes CAM (Chart Accessibility Module), which aims to reduce time and bridge the knowledge gap required to implement chart accessibility. CAM has two steps, generating chart summary using raw data and feeding it to the screen-reader using the Android Accessibility API for MPAndroidChart library. The user study results show that CAM significantly reduces difficulty and time taken to implement accessibility for application developers.

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  1. Bar-JEPA: Extracting Values from Bar Chart with Joint-Embedding Predictive Architecture

    cs.CV 2026-08 conditional novelty 6.0 of 10

    A JEPA encoder finetuned on synthetic bar charts enables a lightweight decoder to recover bar values from chart images, but the method remains behind state-of-the-art supervised systems.

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