Since people with visual impairments find it difficult to understand memes even with the help of screen reader software, researchers designed a new tool that will enable them to enjoy memes.
Researchers at Carnegie Mellon University have developed a method to automatically identify memes and apply prewritten templates to add descriptive alt text, making them intelligible via existing assistive technologies.
Memes are images that are copied and then overlaid with slight variations of text. They are often humorous and convey a shared experience, but “if you’re blind, you miss that part of the conversation,” said Cole Gleason, a PhD student in CMU’s Human-Computer Interaction Institute (HCII.)
“Memes may not seem like the most important problem, but a vital part of accessibility is not choosing for people what deserves their attention,” said Jeff Bigham, associate professor in the HCII. “Many people use memes, and so they should be made accessible.”
Memes largely live within social media platforms that have barriers to adding alt text.
ALSO READ: Google Earth’s new tool lets you ‘personalise your journey’ on the…
Twitter, for example, allows people to add alt text to their images, but that feature isn’t always easy to find. Of 9 million tweets the CMU researchers examined, one million included images and, of those, just 0.1 per cent included alt text.
Gleason said basic computer vision techniques make it possible to describe the images underlying each meme, whether it be a celebrity, a crying baby, a cartoon character or a scene such as a bus upended in a sinkhole.
Optical character recognition techniques are used to decipher the overlaid text, which can change with each iteration of the meme, reported the study published in – Access.
For each meme type, it’s only necessary to make one template describing the image, and the overlaid text can be added for each iteration of that meme.
But writing out what the meme is intended to convey proved difficult.
“It depended on the meme if the humour translated. Some of the visuals are more nuanced,” Gleason said. “And sometimes it’s explicit and you can just describe it.” For example, the complete alt text for the so-called “success kid” meme states “Toddler clenching fist in front of the smug face. Overlaid text on top: Was a bad boy all year. Overlaid text on bottom: Still got awesome presents from Santa.”
The team also created a platform to translate memes into sound rather than text. Users search through a sound library and drag and drop elements into a template. This system was made to translate existing memes and convey the sentiment through music and sound effects.
(With ANI inputs)