Speaking, Seeing, Understanding: Correlating semantic models with conceptual representation in the brain

Luana Bulat, Stephen Clark, Ekaterina Shutova


Abstract
Research in computational semantics is increasingly guided by our understanding of human semantic processing. However, semantic models are typically studied in the context of natural language processing system performance. In this paper, we present a systematic evaluation and comparison of a range of widely-used, state-of-the-art semantic models in their ability to predict patterns of conceptual representation in the human brain. Our results provide new insights both for the design of computational semantic models and for further research in cognitive neuroscience.
Anthology ID:
D17-1113
Volume:
Proceedings of the 2017 Conference on Empirical Methods in Natural Language Processing
Month:
September
Year:
2017
Address:
Copenhagen, Denmark
Venue:
EMNLP
SIG:
SIGDAT
Publisher:
Association for Computational Linguistics
Note:
Pages:
1081–1091
Language:
URL:
https://www.aclweb.org/anthology/D17-1113
DOI:
10.18653/v1/D17-1113
Bib Export formats:
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PDF:
http://aclanthology.lst.uni-saarland.de/D17-1113.pdf
Video:
 https://vimeo.com/238235824