Modern deep neural networks achieve impressive performance in engineering applications
that require extensive linguistic skills, such as machine translation. This success has …

Natural language processing (NLP) is a theory-motivated range of computational techniques
for the automatic analysis and representation of human language. NLP research has …

The authors studied the operation of working memory in language comprehension by
examining the reading of complex sentences. Reading time and comprehension accuracy in …

Many recent models of language comprehension have stressed the role of distributional
frequencies in determining the relative accessibility or ease of processing associated with a …

This article provides an overview of a probabilistic constraints framework for thinking about
language acquisition and processing. The generative approach attempts to characterize …

Speech errors follow the phonotactics of the language being spoken. For example, in
English, if [n] is mispronounced as [], the [] will always appear in a syllable coda. The authors …

In contrast to other approaches, the methods to be described here concentrate primarily on
the conceptual content, the knowledge conveyed in an essay, rather than its grammar, style …

The acquisition of English noun and verb morphology is modeled using a single‐system
connectionist network. The network is trained to produce the plurals and past tense forms of …

In the present study, we sought to advance the field of learner corpus research by tracking
the development of phrasal vocabulary in essays produced at two different points in time. To …

Computational psycholinguistics is concerned with the development of computational
models of the cognitive mechanisms and representations that underlie language processing …