Automated accessibility evaluation will have an increasingly important role in the near future due to legal requirements to monitor the accessibility of the websites of public bodies in the European Union. However, automated evaluation tools are still limited in the scope of the conformance testing they are able to perform. Future solutions resorting to AI based techniques might help in addressing some of these limitations. In this paper we present an updated version of an algorithm that classifies the quality, from an accessibility perspective, of alternative texts for images in web pages. We evaluated the proposed algorithm on a set of 149 images and their corresponding alternative texts and found improved performance compared to the initial version of the algorithm.
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