Affiliation:
1. University of Luxembourg, Esch-sur-Alzette, Luxembourg
2. Aalto University, Espoo, Finland
Abstract
Being able to describe any user interface (UI) screenshot in natural language can promote understanding of the main purpose of the UI, yet currently it cannot be accomplished with state-of-the-art captioning systems. We introduce XUI, a novel method inspired by the global precedence effect to create informative descriptions of UIs, starting with an overview and then providing fine-grained descriptions about the most salient elements. XUI builds upon computational models for topic classification, visual saliency prediction, and natural language generation (NLG). XUI provides descriptions with up to three different granularity levels that, together, describe what is in the interface and what the user can do with it. We found that XUI descriptions are highly readable, are perceived to accurately describe the UI, and score similarly to human-generated UI descriptions. XUI is available as open-source software.
Funder
Horizon 2020 FET program of the European Union through the ERA-NET Cofund funding
European Innovation Council Pathfinder program
Academy of Finland
Publisher
Association for Computing Machinery (ACM)
Subject
Artificial Intelligence,Theoretical Computer Science
Cited by
2 articles.
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1. Boosting GUI Prototyping with Diffusion Models;2023 IEEE 31st International Requirements Engineering Conference (RE);2023-09
2. Enabling Conversational Interaction with Mobile UI using Large Language Models;Proceedings of the 2023 CHI Conference on Human Factors in Computing Systems;2023-04-19