4 accepted papers
Alzheimer’s Disease (AD) is a significant and growing public health concern. Investigating alterations in speech and language patterns offers a promising path towards cost-effective and non-invasive early detection of AD on a large scale. Large language models (LLMs), such as GPT, have enabled power…
Alzheimer’s disease (AD) represents a major problem for society and a heavy burden for those affected. The study of changes in speech offers a potential means for large-scale AD screening that is non-invasive and inexpensive. Automatic Speech Recognition (ASR) is necessary for a fully automated syst…
The collection of eye gaze information provides a window into many critical aspects of human cognition, health and behaviour. Additionally, many neuroscientific studies complement the behavioural information gained from eye tracking with the high temporal resolution and neurophysiological markers pr…
We present a new dataset and benchmark with the goal of advancing research in the intersection of brain activities and eye movements. Our dataset, EEGEyeNet, consists of simultaneous Electroencephalography (EEG) and Eye-tracking (ET) recordings from 356 different subjects collected from three differ…