“Alexa, call Mom” 

This may be a command that most people use sparingly, say when they’re driving or eating food, but there is a global community of over one billion disabled people for whom summoning Alexa, or any of its cousins, is the only way to perform certain basic activities – like calling their Mom. 

A voice assistant like Siri or Alexa, powered by an NLP engine, may be just another cool feature for the majority of us folks. But it is an essential tool to empower those with visual or motor disabilities to live a fuller life by engaging with technology.

Most aspects of life involve communications with others — understanding and being understood by people. Many of us take this understanding for granted, but you can imagine the extreme difficulty and frustration you’d feel if people couldn’t easily decipher the way you talked or expressed yourself. Therefore, NLP has useful applications for people with speech, cognitive or learning disabilities as well.

"Designing for people with disabilities doesn't just benefit those with disabilities. It benefits us all." Jenny Lay-Flurrie, Chief Accessibility Officer, Microsoft.

Natural Language Processing simply deals with the interaction between humans and computers, using a natural language such as English; except that NLP algorithms can’t read text like we do, but they can look for patterns and they find these patterns by turning huge amounts of text into matrices. By applying machine learning algorithms to both text and speech, language technology results in applications such as voice assistants, ASR engines, and speech analytics tools. One of its most widely used applications is machine translation, which automatically translates text or speech from one language to another. In addition, Natural Language Processing is a powerful enabler for assistive technology.

Noteworthy initiatives

AI for Accessibility is a program by Microsoft to improve the lives of persons with disabilities through initiatives such as Seeing AI. Microsoft has also partnered with other organisations to develop technologies that can be used to help autistic children communicate, and to enable deaf and hard of hearing students participate in college lectures through automatic speech recognition. 

Project Euphonia team at Google is using AI to improve computers’ abilities to understand diverse speech patterns, such as impaired speech. They’ve also partnered with ALS organisations to learn about the communication needs of people with ALS, and worked toward optimizing AI based algorithms so that mobile phones and computers can more reliably transcribe words spoken by people with these kinds of speech difficulties.

The risk of bias in NLP algorithms

Despite that over one billion individuals (about 15% of the world’s population) are persons with disabilities (PWD), disability is sometimes the subject of strong negative social biases. A recent paper studied how social biases about persons with disabilities can be perpetuated by NLP models. Entitled "Social Biases in NLP Models as Barriers for Persons with Disabilities", it also mentions recommended and non-recommended phrases to refer to PWDs. This is important for building equitable and inclusive NLP technologies. At the interface of NLP and disability, there is a lot more work to be done to ensure that these technologies integrate seamlessly with and enhance the lives of our differently abled friends.

Image by Marcus Aurelius from Pexels