Researchers at the University of California recently created a self-powered throat patch that uses machine learning to translate muscle movements into speech, helping people to speak without vocal cords.
Jun Chen, an assistant professor of bioengineering at the University of California, Los Angeles, came up with the idea for a non-invasive speech-enabling device after feeling his vocal cords get tired as a result of lecturing for several hours at a time. He began thinking of ways of helping a person speak without using their vocal cords, and with the help of his colleagues at the University of California, he designed an innovative patch that sticks to the user’s throat and uses AI technology to decode their muscle movements into speech. The lightweight device is resistant to skin sweat and also harnesses the user’s muscle movements to generate electricity, which means that it doesn’t require a battery to operate.
