What is digital accessibility?

The world now rests on a digital platform, and avoiding all things digital is impossible. Whether it’s online or offline, content now lives on a digital machine, readily available at just the click of a mouse. But is it accessible to all? What about those with vision or motor impairments? Can they access the same as everyone else?

That’s where digital accessibility comes in – the principle of creating digital content to be as reachable as possible to as many people as possible. Everyone has the right to participate in our digital world, and with the right technologies, websites and software can be altered to serve this purpose.

What is machine learning?

The more a computer knows about you, the more it can adapt itself to your needs. Sounds futuristic, but this incredible technology is making eLearning more streamlined for users. Machine learning learns by making predications on the future based on the data it has already seen. In other words, while you’re working, it’s quietly observing, and making changes to its algorithm as it progresses. 

4 ways to use machine learning to improve digital accessibility

In an ever evolving world, the workforce is now diverse. It’s due to this inclusivity that digital accessibility becomes as widespread as possible. Our HowToo Xperts believe strongly that all learners should be able to access and engage with our courses, and the only way to do this is to improve the accessibility of digital content.

Unfortunately, finding the right technology products can take time and cost money, which is why we’re looking at other solutions. Let’s take a look at four ways we can use machine learning to improve digital accessibility:

#1 Automated subtitles

First, let’s look at the difference between subtitles and closed captions. Subtitles focus on translating and displaying spoken words, used mostly when watching foreign movies. Closed captions are written text lines at the bottom of a video that describe all the audio, including speech, and background music. Closed captions, in other words, are used for those who are hearing impaired. 

Video streaming platforms are becoming increasingly adept at using speech recognition technology and algorithms for better viewing experience for the hearing impaired. It’s great to see that machine learning is improving all the time, and algorithms can now identify music, applause, and background chatter that it might not have picked up on before.

#2 Automated image descriptions

Alt-text offers text descriptions of images for those who are visually impaired. The alt-text is usually hidden, but is read out loud when using a screen reader. It’s something that requires human processing, but machine learning is slowly allowing for a more precise automation. In 2016, Facebook launched an image recognition feature based on its research that enables text descriptions to be automatically generated for images. In other words, if a friend posted a photo, this would be described to them via text descriptions read out loud through the use of a text to speech software. 

Image recognition is becoming an increasingly powerful tool, and there are now adaptive learning delivery capabilities that use facial recognition to identify a learner’s response to their experience. In other words, if you look like you are struggling it might suggest a less challenging topic. Or, if you’re relaxed and smiling, and going through the content quickly, it will offer something a little more challenging.

#3 Simplification software 

It’s important not to get left behind in a world that is increasingly digitally centric. With the rise of online devices, people are becoming more and more reliant on communication via computers and mobile devices. While this might be good for some, it also means that those with learning or intellectual difficulties could struggle to keep up with the constant changes. 

Simplification software can be used for this. It can be built directly into apps or simply integrated with commonly used platforms. The basic premise is that it can improve readability by breaking up lengthy sentences, and replacing complex terms or sentences with easier to understand words and phrases. 

Automated learning interventions

As with any facet in life, early intervention is the key to a positive outcome, and the same can be said with learning difficulties. Machine learning might be the key to correctly identify any learning difficulties as early as possible so that an alternate learning solution can be offered. 

Educational possibilities provide a great reach by including computer based or eLearning content. However, it’s important to ensure that no student is left behind.

Recent research has found that children who are affected by neural disorders which affect speech or comprehension often display similar patterns when performing set tasks. Automated screening tools can be used to ask children to narrate a series of pictures, and it is through their pauses, struggles with tenses, or language patterns, where known difficulties will be shown. It is with this data that early intervention can take place, to allow for the correct level of challenge to be set. 

An automated future?

As society becomes more and more digital-based, many people risk being unfairly excluded on the basis of a disability. By providing your workplace with accessible digital content, you’re creating a more inclusive and richer future.

Check if your digital content is accessible by downloading our FREE Accessibility Checklist. This will show you exactly where you are thriving, as well as where you could improve.