At Johns Hopkins University, linguistics is fully integrated into the Department of Cognitive Science. Our research focuses on integrating formal linguistics within a broader cognitive science perspective by addressing questions about the nature of linguistic representations themselves, their processing, the architecture and learnability of the grammar, the implementation of linguistic theories in terms of neural computations, as well as language emergence and language acquisition in the broader context of cognitive development.
The department offers basic and advanced undergraduate and graduate training covering all core areas including:
- Phonetics and phonology
- Syntax
- Semantics and pragmatics
- Psycholinguistics
- Neurolinguistics
- Acquisition
- Computational linguistics
Linguistics Faculty
- John Hale: psycholinguistics, neurolinguistics, computational linguistics
- Annemarie Kocab: language emergence, language acquisition, language processing, sign languages
- Barbara Landau: language acquisition, language and thought, cognitive neuropsychology of language
- Geraldine Legendre: syntax, acquisition of L1 (morpho)-syntax, architecture of the grammar
- Kyle Rawlins: semantics/pragmatics, mathematical and computational linguistics
- Peggy Renwick: sociophonetics, laboratory phonology, phonetics, speech acoustics
- Paul Smolensky: phonology, grammar in neural networks, formal foundations of cognitive science
- Colin Wilson: phonology, phonetics, statistical language learning, L2 speech perception and production
- Julia Yarmolinskaya: perception and acquisition of second language phonology
Faculty With Language-related Interests
- Mike McCloskey: representation and processing of written and spoken words, cognitive neuropsychology of language
- Brenda Rapp: representation and processing of written and spoken words, cognitive neuropsychology of language
Non-Departmental Faculty
Department of Psychological & Brain Sciences
- Marina Bedny: brain development and plasticity, cognitive neuroscience, concepts
- Lisa Feigenson: cognitive development in infancy, working memory, knowledge of number
- Justin Halberda: logical reasoning in children, visuo-spatial representation, knowledge of number
- Chris Honey: computational cognitive neuroscience
Center for Language & Speech Processing
- Mark Drezde: natural language processing (NLP)
- Jason Eisner: computational linguistics, NLP
- Hynek Hermansky: automatic speech recognition, speech production and perception
- Sanjeev Khudanpur: automatic speech recognition, NLP, machine translation)
- Benjamin Van Durme: computational semantics
- David Yarowsky: NLP, machine translation, machine learning
Undergraduate Training in Linguistics
Undergraduate students may select linguistics as one of two foci for their BA in cognitive science, or add a minor in linguistics to another degree. A significant number of BA recipients have gone on to pursue graduate studies in formal linguistics in top departments around the country.
Graduate Training in Linguistics
Doctoral graduate training includes a rotation in two labs/groups covering multiple methodologies in cognitive science (e.g., theory and experiments, experiments and computation), and typically multiple empirical domains, coursework in formal methods, and coursework in a sub-discipline (e.g., linguistics, cognitive psychology).
All graduate student research on linguistic problems benefits from solid training in linguistic theory and analysis combined with a broad background in cognitive science. Among the language-focused faculty are linguists as well as cognitive psychologists and computer scientists who share a broad intellectual vision of the study of the mind.
Historical Perspective on Generative Linguistics
Since Noam Chomsky’s proposal in the 1950s that the object of study in linguistics is a uniquely human mental capacity, linguistics has been one of the core disciplines of cognitive science.
Generative/formal linguistics has focused on uncovering the nature of representations and general principles underlying linguistic behavior at distinct levels of structure (e.g., phonology, syntax, semantics), and has attempted to understand what type of knowledge and predispositions children are born with in order to successfully learn their first language.
Formal linguistics has been quite successful at discovering the nature of linguistic representations and accounting for the complexity of linguistic knowledge. Viewing language in the broader context of cognitive science brings to light many important questions that traditional types of data and methods do not fully address: Does linguistic cognition share key computational properties with other cognitive domains? What is the nature of the algorithm that makes real-time language comprehension and production possible? How is linguistic computation implemented in the brain?
We are now at the beginning of an exciting era in which the traditional analysis of linguistic representation and computation is being integrated with other research areas and methods in an effort to answer such questions. Formal linguistics remains an active and fruitful research area, one that will realize its full potential by contributing to the broader goals of cognitive science.