Abstract
Audio rendering of mathematical expressions has accessibility benefits for people with visual impairment. Seeking a systematic way to measure participants’ perception of the rendered formulae with audio cues, we investigate the design of performance metrics to capture the distance between reference and perceived math expressions. We propose EAR-Math, a methodological approach for user-based evaluation of math rendering against a baseline. EAR-Math measures systems’ performance using three fine-grained error rates based on the structural elements, arithmetic operators, numbers and identifiers in a formula. The proposed methodology and metrics were successfully applied in a pilot study, where 5 sighted and 2 blind participants evaluated 39 stimuli rendered by MathPlayer in Greek. In the obtained results, we observed that structural elements had the highest mean and variance of errors, which improved from 18% in the first attempt to 10% and 7% in two following attempts.
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Kacorri, H., Riga, P., Kouroupetroglou, G. (2014). EAR-Math: Evaluation of Audio Rendered Mathematics. In: Stephanidis, C., Antona, M. (eds) Universal Access in Human-Computer Interaction. Universal Access to Information and Knowledge. UAHCI 2014. Lecture Notes in Computer Science, vol 8514. Springer, Cham. https://doi.org/10.1007/978-3-319-07440-5_11
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DOI: https://doi.org/10.1007/978-3-319-07440-5_11
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