Data-driven models and computational tools for neurolinguistics: a language technology perspective
Machine Learning
2020-03-25 v1 Computation and Language
Machine Learning
Abstract
In this paper, our focus is the connection and influence of language technologies on the research in neurolinguistics. We present a review of brain imaging-based neurolinguistic studies with a focus on the natural language representations, such as word embeddings and pre-trained language models. Mutual enrichment of neurolinguistics and language technologies leads to development of brain-aware natural language representations. The importance of this research area is emphasized by medical applications.
Cite
@article{arxiv.2003.10540,
title = {Data-driven models and computational tools for neurolinguistics: a language technology perspective},
author = {Ekaterina Artemova and Amir Bakarov and Aleksey Artemov and Evgeny Burnaev and Maxim Sharaev},
journal= {arXiv preprint arXiv:2003.10540},
year = {2020}
}
Comments
37 pages, 1 figure