Automatic Checking of Alternative Texts on Web Pages

Olsen, Morten Goodwin; Snaprud, Mikael; Nietzio, Annika

doi:10.1007/978-3-642-14097-6_68

Cited by 6 publications

(4 citation statements)

References 6 publications

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“…A discussion on descriptive vs undescriptive alt-texts can be found in [16] where the authors propose two approaches to automatically detect undescriptive alt-texts in web pages using pattern recognition algorithms. To get the data used for the classification, they analyzed the home pages of more than 400 Norwegian municipalities.…”

Section: Evaluating Alternative Textsmentioning

confidence: 99%

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Evaluating the effectiveness of automatic image captioning for web accessibility

Leotta

Mori

Ribaudo

2022

Univ Access Inf Soc

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The web has become a fundamental tool for carrying out many activities spanning from education to work and private life. For this reason, it must be accessible to every user regardless of any form of impairment or disability. Images on the web are a primary means for communicating information, and specific HTML elements were defined to enrich images with textual descriptions, which can be read aloud by screen readers or rendered by braille displays. A relevant problem is that adding a text describing each image published on a website is a demanding task requiring a non-negligible effort for web developers. Several tools based on machine learning have emerged, which can automatically return descriptions for the images. In this work, we evaluate the correctness of their outputs by comparing the generated descriptions with human-defined references. More specifically, we selected 60 images from Wikipedia and their corresponding descriptions as defined by Wikipedia contributors. We then generated the corresponding descriptions employing four state of the art tools (Azure Computer Vision Engine, Amazon Rekognition, Cloudsight, and Auto Alt-Text for Google Chrome) and asked 76 computer science students to blindly evaluate the perceived correctness of the descriptions without being aware of their source. The results show that the descriptions available in Wikipedia are still perceived as the best ones. However, some tools generate good results for specific categories of images, and they can represent proper candidates for the automated and massive addition of image descriptions to websites, helping to increase the accessibility level of the web drastically.

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Section: Evaluating Alternative Textsmentioning

confidence: 99%

“…A web developer willing to try Azure CVE can call a REST API which is available online 16 . By uploading an image as input, the AI algorithms process it and return a JSON file with the answer, e.g., a description composed of tags and complete sentences, with different confidence levels (see a portion in Table 1).…”

Section: Azure Computer Vision Enginementioning

confidence: 99%

Evaluating the effectiveness of automatic image captioning for web accessibility

Leotta

Mori

Ribaudo

2022

Univ Access Inf Soc

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“…Prior work on machine checking of image text equivalents have focused on image OCR or text pattern recognition techniques (e.g., dictionary-based word search, file type abbreviations, HTML code, number of characters) to automatically identify what should not be present in appropriate text alternatives [4,15,24]. The size of the image has also been used as a reference to detect non-accessible images [5], classifying as informative (and thus in need of alt) those bigger than 10 x 10 pixels, and then automatically giving them text alternatives based on web content analysis, OCR and human labelling (ibid).…”

Section: Evaluation and Repairmentioning

confidence: 99%

Measuring the impact of automated evaluation tools on alternative text quality

Vázquez

2016

Proceedings of the 13th International Web for All Conference

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The number of Internet users has increased tenfold since the beginning of the century up to present, especially thanks to the improvements experienced in web accessibility and the growing number of languages which online content is available in. While translation professionals are making a considerable contribution to that digital information richness, little evidence exists regarding their involvement in the achievement of a more accessible web for all. In this paper, we present the main results of the first empirical study on web accessibility conceived around a translation task. The experiment sought to particularly investigate the quality of image text alternatives produced by French translators with the help of two evaluation tools: aDesigner and Acrolinx. The assessment of their alt text proposals, carried out by seven screen reader users, suggests that using both tools helps translators to create more appropriate text alternatives than when trying to do so with only one tool or without any automated support. A more in-depth analysis of the data gathered shows that Acrolinx offers better guidance than aDesigner for translators to render images accessible.

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“…In terms of accessibility best practice, if the image serves no purpose (such as being a part of a clickable link) then snippet 2 would be acceptable, generally indicating to the user that the image is largely decorative in nature (WebAIM, 2014). In the context of this explanation, snippet 4 would provide the most relevant information to the user without adding undue cognitive load (Olsen, et al, 2010) in terms of excessive explanation of the image content.…”

Section: Robustmentioning

confidence: 99%

The challenges of Web accessibility: The technical and social aspects of a truly universal Web

Brown

Hollier²

2015

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This paper explores the concept of Web accessibility and how technologies, guidelines and policies have evolved since the turn of the twenty-first century in order to address the ideals of equitable access to online content for all people. The paper discusses the high availability of assistive technologies built into consumer devices and the associated accessibility guidelines for Web sites and content. Through examination of the literature, this paper shows that the accessible design and assessment of Web sites can be complicated, and that social media, corporate and government Web sites are yet to fully realise the goals of an accessible Web. The paper concludes with the view that disability awareness, more than technology and policy, is perhaps the primary obstacle to a more universally accessible Web.

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Automatic Checking of Alternative Texts on Web Pages

Cited by 6 publications

References 6 publications

Evaluating the effectiveness of automatic image captioning for web accessibility

Evaluating the effectiveness of automatic image captioning for web accessibility

Measuring the impact of automated evaluation tools on alternative text quality

The challenges of Web accessibility: The technical and social aspects of a truly universal Web

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