Academics | Johns Hopkins University
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MS in Information Systems
With the Johns Hopkins Carey Business School's MS in Information Systems, you'll leverage the latest technology to make…
The rigorous curriculum focuses on the fundamentals of computer science, statistics, and applied mathematics, while…
Computer Science | Whiting School of Engineering
What is Computer Science? Computer science is a fast-growing, rapidly evolving field. It spans the theoretical to the…
Related Centers & Institutes
- Institute for Computational Medicine (ICM)
- Institute for Data Intensive Engineering and Science (IDES)
- Johns Hopkins University Information Security Institute (JHUISI)
- Johns Hopkins Systems Institute
- Laboratory for Computational Sensing and Robotics
- Center for Language and Speech Processing
- Center for Computational Biology
- Center for Population Health Information Technology
- Science of Learning Institute
- Computer Engineering undergraduate and graduate programs
- Robotics full-time master’s program
- Master of Science in Security Informatics Program
- Cybersecurity part-time and online graduate degree programs (Engineering for Professionals)
- Information Systems part-time and online graduate degree programs (Engineering for Professionals)
Courses | Center for Language and Speech Processing
Computer Science 600.465 Natural Language Processing: Prof. Eisner 600.466 Information Retrieval and Web Agents: Prof…
The Johns Hopkins Center for Language and Speech Processing (CLSP) was established at Johns Hopkins University in 1992 with support from the U.S. government (NSF, DARPA, DoD). Its aim is to promote research and education in the science and technology of language and speech.
- 600.465 Natural Language Processing: Prof. Eisner
- 600.466 Information Retrieval and Web Agents: Prof. Yarowsky
- 600.468 Machine Translation: Dr. Lopez, Dr. Post
- 600.765 Selected Topics in Natural Language Processing: Prof. Eisner
- 600.766 Selected Topics in Meaning, Translation and Generation of Text: Prof. Van Durme
Electrical and Computer Engineering
- 520.315 Introduction to Information Processing of Sensory Signals: Prof. Hermansky
- 520.445 Introduction to Speech and Audio Processing: Prof. Elhilali
- 520.447 Introduction to Information Theory and Coding: Prof. Karakos
- 520.666 Information Extraction from Speech and Text: Prof. Khudanpur
- 520.680 Speech and Auditory Processing by Humans and Machines: Prof. Hermansky
- 520.702 Current Topics in Language and Speech Processing: Prof. Khudanpur and Prof. Karakos
- 520.735 Sensory Information Processing: Prof. Andreou
- 050.370/670 Formal Methods in Cognitive Science: Language Prof. Rawlins
- 050.371/671 Formal Methods in Cognitive Science: Inference Prof. Smolensky
- 050.372/672 Formal Methods in Cognitive Science: Neural Networks Prof. Smolensky
- 050.317/617 Semantics I
- 050.320/620 Syntax I
- 050.321/621 Syntax II
- 050.325/625 Phonology I Prof. Wilson
- 050.327/627 Phonology II
- 050.330 Psycholinguistics
- 050.630 Topics in Language Processing
- Please see the list of courses at JHU’s machine learning website. Many of these courses are taken by CLSP students, and some are taught by CLSP faculty.
Linguistics at JHU | Cognitive Science | Johns Hopkins University
At Johns Hopkins University, linguistics is fully integrated into the Department of Cognitive Science. Our research…
Linguistics at JHU
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, and language acquisition in the broader context of cognitive development.
In 2010, the National Research Council ranked us as one of the top departments in the country in which to study linguistics.
The department offers basic and advanced undergraduate and graduate training covering all core areas including:
- Phonetics and phonology
- Semantics and pragmatics
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.