If you run a website, you may know that adding alt text to images you post is important for SEO and site ranking. However, alternative text is also essential for screen readers to convert text to speech for describing images to visually impaired users. Despite this, the majority of images online don’t have alt text. Microsoft wants to change this with Microsoft Edge.
When there is no alt text on an image, a screen reader will describe the image as an “unlabeled graphic” to users. The is hardly useful. In Microsoft Edge, the browser now has an update for its screen reader that will boost its functionality on images without alternative text:
“When a screen reader finds an image without a label, that image can be automatically processed by machine learning (ML) algorithms to describe the image in words and capture any text it contains,” says Travis Leithead, a program manager on Microsoft’s Edge platform team. “The algorithms are not perfect, and the quality of the descriptions will vary, but for users of screen readers, having some description for an image is often better than no context at all.”
Unlabeled images are sent to Microsoft Azure. Specifically, the computer vision API, where Azure will process the images. It can create alt text from images providing descriptions that are otherwise missing. The API supports English, Spanish, Portuguese, Japanese, and Simplified Chinese.
Microsoft says all its processing adheres to its privacy commitments. However, the API won’t handle all images. Those smaller 50 x 50 pixels, decorative images, very large files, or images Azure classifies as gory, sexually suggestive, or pornographic will not be processed.
The good news is this new feature is landing on Microsoft Edge starting today. No preview, just straight up availability across Windows, Mac, and Linux. Microsoft points out the feature is not available on iOS or Android but will be in the future. Head to edge://settings/accessibility to see the tool for yourself.
“This feature is still new, and we know that we are not done,” adds Leithead. “We’ve already found some ways to make this feature even better, such as when images do have a label, but that label is not very helpful. Continuous image recognition and algorithm improvements will also refine the quality of the service.”
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