Sonify: Making Visual Graphs Accessible

Ali, Safinah; Muralidharan, Laya; Alfieri, Felicia; Agrawal, Monali; Jørgensen, Jacob Høj

doi:10.1007/978-3-030-25629-6_70

Cited by 7 publications

(5 citation statements)

References 5 publications

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“…Lyu et al [20] apply an interactive virtual environment that allows real time tweaking of a neural network's hyperparameters by providing users with auditory feedback on the impact of their choices. Finally, [1] highlights the shortcomings of visual representations for non-trained and visually impaired individuals, and suggest sonification as one of the prevalent alternatives.…”

Section: Related Workmentioning

confidence: 98%

SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms

Asonitis¹,

Allmendinger²,

Benatan³

et al. 2022

Preprint

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We propose SonOpt, the first (open source) data sonification application for monitoring the progress of bi-objective populationbased optimization algorithms during search, to facilitate algorithm understanding. SonOpt provides insights into convergence/stagnation of search, the evolution of the approximation set shape, location of recurring points in the approximation set, and population diversity. The benefits of data sonification have been shown for various non-optimization related monitoring tasks. However, very few attempts have been made in the context of optimization and their focus has been exclusively on single-objective problems. In comparison, SonOpt is designed for biobjective optimization problems, relies on objective function values of non-dominated solutions only, and is designed with the user (listener) in mind; avoiding convolution of multiple sounds and prioritising ease of familiarizing with the system. This is achieved using two sonification paths relying on the concepts of wavetable and additive synthesis. This paper motivates and describes the architecture of SonOpt, and then validates SonOpt for two popular multi-objective optimization algorithms (NSGA-II and MOEA/D). Experience SonOpt yourself via https://github.com/tasos-a/SonOpt-1.0.

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Section: Related Workmentioning

confidence: 98%

SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms

Asonitis¹,

Allmendinger²,

Benatan³

et al. 2022

Preprint

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show abstract

“…Siu et al [45] propose an automated method for splitting a line chart into several sequences and adding a template-based alternative text to each sequence. Agarwal et al [4] provide a touch-based interaction method for browsing data sonifications on mobile phones. While prior sonification research has focused on use of non-speech sound, accessibility studies underscore combining speech and nonspeech sound to design audio charts.…”

Section: Sonification Tools and Toolkitsmentioning

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%

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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“…For decades, image sonification has communicated spatial information to blind or low-vision (BLV) individuals (Meijer, 1992;Yeo and Berger, 2005;Zhang et al, 2014). It is also used for audio alerts (i.e., Geiger counters; Kramer et al, 2010), research (i.e., studying brain wave changes; Parvizi et al, 2018), communications and education (i.e., multimedia cosmology sonification; Ballora and Smoot, 2013), increasing accessibility (i.e., the sonification of visual graphs; Ali et al, 2020), and for art and entertainment (i.e., compositional works based upon neurological or cosmic particle data; Sinclair, 2012).…”

Section: Sonification Overviewmentioning

confidence: 99%

A Universe of Sound: processing NASA data into sonifications to explore participant response

Arcand,

Schonhut-Stasik,

Kane

et al. 2024

Front. Commun.

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IntroductionHistorically, astronomy has prioritized visuals to present information, with scientists and communicators overlooking the critical need to communicate astrophysics with blind or low-vision audiences and provide novel channels for sighted audiences to process scientific information.MethodsThis study sonified NASA data of three astronomical objects presented as aural visualizations, then surveyed blind or low-vision and sighted individuals to elicit feedback on the experience of these pieces as it relates to enjoyment, education, and trust of the scientific data.ResultsData analyses from 3,184 sighted or blind or low-vision survey participants yielded significant self-reported learning gains and positive experiential responses.DiscussionResults showed that astrophysical data engaging multiple senses could establish additional avenues of trust, increase access, and promote awareness of accessibility in sighted and blind or low-vision communities.

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Sonify: Making Visual Graphs Accessible

Cited by 7 publications

References 5 publications

SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms

SonOpt: Sonifying Bi-objective Population-Based Optimization Algorithms

Erie: A Declarative Grammar for Data Sonification

A Universe of Sound: processing NASA data into sonifications to explore participant response

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