TactualPlot: Spatializing Data as Sound using Sensory Substitution for Touchscreen Accessibility

Chundury, Pramod; Reyazuddin, Yasmin; Jordan, J. Bern; Lazar, Jonathan; Elmqvist, Niklas

doi:10.1109/tvcg.2023.3326937

Cited by 5 publications

(2 citation statements)

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“…add ( bin ) ; 11 // Add the count aggregation 12 let aggregate = new Aggregate () ; 13 // setting operation and the new field name -> setting group -by 14 aggregate . add (" count " , " count " ) 15 . groupby ([ " miles -per -gallon " ]) ; 16 spec .…”

Section: Spec Apimentioning

confidence: 99%

“…A prerequisite to developing an interactive grammar for data sonification is some understanding of how a sonification listener would trigger a user interaction and receive its feedback using different modalities. For instance, various approaches to using a keyboard, speech recognition, tabletop screens, or mobile haptic screens for interactive sonification are fruitful topics like personalized sonifications for future research to explore (e.g., [4,15]).…”

Section: Future Workmentioning

confidence: 99%

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Erie: A Declarative Grammar for Data Sonification

Kim,

Hullman

2024

Proceedings of the CHI Conference on Human Factors in Computing Systems

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Data sonification-mapping data variables to auditory variables, such as pitch or volume-is used for data accessibility, scientific exploration, and data-driven art (e.g., museum exhibitions) among others. While a substantial amount of research has been made on effective and intuitive sonification design, software support is not commensurate, limiting researchers from fully exploring its capabilities. We contribute Erie, a declarative grammar for data sonification, that enables abstractly expressing auditory mappings. Erie supports specifying extensible tone designs (e.g., periodic wave, sampling, frequency/amplitude modulation synthesizers), various encoding channels, auditory legends, and composition options like sequencing and overlaying. Using standard Web Audio and Web Speech APIs, we provide an Erie compiler for web environments. We demonstrate the expressiveness and feasibility of Erie by replicating research prototypes presented by prior work and provide a sonification design gallery. We discuss future steps to extend Erie toward other audio computing environments and support interactive data sonification. CCS CONCEPTS• Human-centered computing → Accessibility systems and tools.

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Section: Spec Apimentioning

confidence: 99%

Section: Future Workmentioning

confidence: 99%