Electroencephalogram (EEG) signal analysis, which is widely used for human-computer
interaction and neurological disease diagnosis, requires a large amount of labeled data for …

NLP models are imperfect and lack intricate capabilities that humans access automatically
when processing speech or reading a text. Human language processing data can be …

Most previous studies integrate cognitive language processing signals (eg, eye-tracking or
EEG data) into neural models of natural language processing (NLP) just by directly …

In this thesis, we aim to narrow the gap between human language processing and
computational language processing. Natural language processing (NLP) models are …

The approach to cognitive plausibility adopted in this book relies heavily on information that
can be drawn from cognitive signals. We introduce a range of cognitive signals that reveal …

Research on assistive technologies is undergoing many developments in its effectiveness in
helping those with varying impairments. New technologies are constantly being created …

We describe a statistical language model having components that are inspired by
electrophysiological activities in the brain. These components correspond to important …

People with movement disabilities will not be able to move around as conveniently and
easily as other people. One of the solutions that can help them is assistive technology based …

We present BCIpy, an open source toolkit 1 written in Python, which focuses on temporal
features in EEG (electroencephalography) recordings from a single channel. BCIpy extracts …