A Framework for Decoding Event-Related Potentials from Text
Computation and Language
2019-04-03 v2
Abstract
We propose a novel framework for modeling event-related potentials (ERPs) collected during reading that couples pre-trained convolutional decoders with a language model. Using this framework, we compare the abilities of a variety of existing and novel sentence processing models to reconstruct ERPs. We find that modern contextual word embeddings underperform surprisal-based models but that, combined, the two outperform either on its own.
Cite
@article{arxiv.1902.10296,
title = {A Framework for Decoding Event-Related Potentials from Text},
author = {Shaorong Yan and Aaron Steven White},
journal= {arXiv preprint arXiv:1902.10296},
year = {2019}
}