Data-driven Models and Computational Tools for Neurolinguistics: a Language Technology Perspective

Ekaterina Artemova, Amir Bakarov, Aleksey Artemov, Evgeny Burnaev, Maxim Sharaev

Research output: Contribution to journalArticlepeer-review

2 Citations (Scopus)

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.

Original languageEnglish
Pages (from-to)15-52
Number of pages38
JournalJournal of Cognitive Science
Volume21
Issue number1
Publication statusPublished - 2020

Keywords

  • BERT
  • brain-aware embeddings
  • distributional semantics models
  • EEG
  • fMRI
  • GloVe
  • natural language representations
  • neuroimaging data
  • neurolinguistics
  • word embeddings
  • word2vec

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