The glove developed by UCLA bio-engineers uses machine learning and a smartphone app to translate American Sign Language to words.
The glove has thin, stretchable sensors on the inside and is able to translate numbers, words and phrases signed by the person wearing it into spoken words in real-time.
The translation is done through a smartphone app using a custom machine-learning algorithm. The system can recognise up to 660 signs so far, including each letter of the alphabet and numbers from zero to nine.
“Our hope is that this opens up an easy way for people who use sign language to communicate directly with non-signers without needing someone else to translate for them,” said Jun Chen, the principal investigator on the glove, in a statement.
“In addition, we hope it can help more people learn sign language themselves.”
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This technology could be very helpful in some circumstances. But a glove or an app probably cannot incorporate facial expression and body language, which are essential elements of ASL.