GazeTalk.AI enables people with aphasia communicate through multimodal interaction and practice evidence-based language therapy at home supported by an AI trained in rehabilitation. GazeTalk.AI is under development at the Technical University of Denmark (DTU), Department of Management.
Aphasia is an acquired language disorder — most commonly caused by stroke — that affects the ability of speaking, reading, writing, and comprehension. Despite the importance of long-term and post-acute rehabilitation processes, the vast majority of people with aphasia often struggle with limited therapist availability, lack of personalization, and poor long-term adherence. Moreover, quality of life of aphasia patients and their family & friends often deteriorates due to breakdown in communication.
GazeTalk.AI combines an Augmentative and Alternative Communication (AAC) system with an AI trained in delivering aphasia rehabilitation in a platform utilizing multimodal interaction (eye gaze, head tracking, speech, and keyboard stroke) — helping patients to communicate via different modes, practice independently, and follow a personalised rehabilitation plan — while keeping clinicians informed through a real-time dashboard.
GazeTalk was first developed at the IT University of Copenhagen in the early 2000s by Prof. John Paulin Hansen and colleagues — originally as a gaze-based communication tool for people with Amyotrophic Lateral Sclerosis (ALS) who had lost the ability to speak and move. The system let users compose text and communicate through eye movements alone, pioneered by foundational work on predictive gaze-based keyboards (Johansen, Hansen & Itoh, 2006).
Today, GazeTalk has evolved. Communication remains at its core — but the platform now adds a new dimension: language rehabilitation. Powered by AI, GazeTalk.AI supports people with aphasia through personalized & independent therapy, helping them not just to communicate, but to recover. This evolution builds on years of peer-reviewed research, including studies on mental fatigue measurement using eye metrics (Bafna & Hansen, 2021) and mental fatigue prediction during eye-typing (Bafna, Bækgaard & Hansen, 2021).
References
Bafna, T., & Hansen, J. P. (2021). Mental fatigue measurement using eye metrics: A systematic literature review. Psychophysiology, 58(6), e13828.
Bafna, T., Bækgaard, P., & Hansen, J. P. (2021). Mental fatigue prediction during eye-typing. PLOS ONE, 16(2), e0246739.
Johansen, A. S., Hansen, J. P., & Itoh, K. (2006). Predictive, restricted on-screen keyboard for gaze communication. In International Conference on Computers Helping People with Special Needs (pp. 555–562). Springer.
GazeTalk.AI serves the clinicians guiding recovery, the patients living it, and the caregivers supporting them.
In 2025, GazeTalk.AI received the Distinguished Innovator Grant by Novo Nordisk Fonden. Currently, GazeTalk.AI is in active pilot development. These goals define our objective to conduct a clinical feasibility study in the period of 2026–2027 in Denmark.
An interdisciplinary team combining expertise in human-computer interaction, clinical natural language processing, machine learning, and aphasia rehabilitation.
We are seeking students and researchers from diverse backgrounds to collaborate with us on GazeTalk.AI. In particular, we actively seek DTU students to do a project/thesis with us. See opportunities below for further detail. Do not see a project that fits? We are always open to new ideas and collaborations. Reach out and let us explore ideas together.