Models that represent meaning as high-dimensional numerical vectors—such as latent
semantic analysis (LSA), hyperspace analogue to language (HAL), bound encoding of the …

Distributional semantics provides multidimensional, graded, empirically induced word
representations that successfully capture many aspects of meaning in natural languages, as …

The discriminative lexicon is introduced as a mathematical and computational model of the
mental lexicon. This novel theory is inspired by word and paradigm morphology but …

This volume provides an introduction to word and paradigm models of morphology and the
general perspectives on linguistic morphology that they embody. The recent revitalization of …

In the last decade, deep artificial neural networks have achieved astounding performance in
many natural language-processing tasks. Given the high productivity of language, these …

In this study we present a novel set of discrimination-based indicators of language
processing derived from Naive Discriminative Learning (ndl) theory. We compare the …

A lively research field has recently emerged that uses experimental methods to probe the
linguistic behaviour of modern deep networks. While work in this tradition often reports …

Recent decades have ushered in tremendous progress in understanding the neural basis of
language. Most of our current knowledge on language and the brain, however, is derived …

In the present study, we leveraged computational methods to explore the extent to which,
relative to direct access to semantics from orthographic cues, the additional appreciation of …

The pervasive use of distributional semantic models or word embeddings for both cognitive
modeling and practical application is because of their remarkable ability to represent the …