The dataset allows researchers to train machine learning models to create graphic labels of varying complexity and content based on user needs. The team discovered that models trained with VisText consistently produce accurate and semantically rich tags that effectively identify data trends and complex patterns.
Angie Boggust and Benny J. Tang, co-authors of the study, believe these advances could improve scheduling accessibility for the visually impaired.
The research will be presented at the annual meeting of the Society for Computational Linguistics.
Source: Ferra
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