A research team of University of Cambridge and the University of Dundee have used an AI driven context aware method to assist non verbal people with motor disabilities who rely on computers to communicate with others.
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What Is This Innovative New Research? In this Artificial Intelligence assisted method, the communication gap faced by non-verbal people is reduced by eliminating between 50% to 96% of the keystrokes each of them has to type to converse.
Developers are making #chatbots more human-like, able to recognize speech patterns and capable of interpreting non-verbal interaction to make the communication even smoother and interactive. https://t.co/4qyE8ylOj4 #chatbot #bot #bots #ai #deeplearning #machinelearning pic.twitter.com/vhbfvFJT5J — Wysh (@WyshApp) September 19, 2018
The system is made using a range of context clues like the user’s location, the time of day, and the identity of the user’s speaking partner. It assists in suggesting sentences that are the most relevant for the particular user and finishing words used in a sentence using the auto-complete function.
Facing The Challenge Of Non-verbal Communication? There exists a difference in communication rates between verbal and non-verbal people, often called the communication gap. Prior research shows that people who rely on speech synthesis tend to reuse many phrases and sentences used in everyday conversations, just like us. However, retrieval of such words is a time-consuming process that further slowing down the flow of conversation.
The communication gap is typically between 80 and 135 words per minute for mute people that affects the quality of their everyday interactions. Prof. Per Ola Kristensson, Study’s Lead Author
In this newly designed system, the information retrieval algorithms are at work as the person is typing. In the process, it automatically retrieves the most relevant previous phrase, keeping in mind the context of the conversation, the given user is involved in. The other speaker is identified using a computer vision algorithm that can recognize human faces from a front-facing camera.
Hope For Future Motor Disability Solutions Individuals with developmental learning disabilities often struggle to be understood. They are reminded every time they try to talk naturally but can’t as other people mostly don’t show the required level of patience and make them uncomfortable enough not to communicate at all with others. Others who persist find that such daily occurrences make them dependent on only human caregivers and support circles who can act as a medium between them and their conversation partner.
How I Trust People With My Non-Verbal Child #parenting #autism #family #dadblogger @HiJamesGuttman https://t.co/Ex6HlgrswY — Hi Blog! I'm Dad. (@HiBlogImDad) June 17, 2020
Such modern mechanisms of assistance can help all people with motor disabilities easily communicate in the future as such advanced and easy to understand and implement AI-user interfaces would now challenge the traditional user interface design processes.
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