World-first tech translates thoughts into text

The technology could aid communication for people who are unable to speak as well as enabling communication between humans and machines, such as in the operation of a bionic arm or robot.

The research was led by Distinguished Professor CT Lin, director of the GrapheneX-UTS Human-centric Artificial Intelligence Centre at the University of Technology Sydney (UTS), together with first author Yiqun Duan and fellow PhD candidate Jinzhou Zhou from the UTS Faculty of Engineering and IT.

In the study participants silently read passages of text while wearing a cap that recorded electrical brain activity through their scalp using an electroencephalogram (EEG).

The EEG wave is segmented into distinct units that capture specific characteristics and patterns from the human brain. This is done by an AI model called DeWave developed by the researchers that translates EEG signals into words and sentences by learning from large quantities of EEG data. 

“This research represents a pioneering effort in translating raw EEG waves directly into language, marking a significant breakthrough in the field,” Professor Lin said in a statement. “It is the first to incorporate discrete encoding techniques in the brain-to-text translation process, introducing an innovative approach to neural decoding. The integration with large language models is also opening new frontiers in neuroscience and AI.”