Winter 2026 - LING 28620, LING 38620, COGS 22015
Course Summary:
This course is a mixed level introduction to topics at the intersection of computation and language. We will study computational linguistics from both scientific and engineering angles: the use of computational modeling to address scientific questions in linguistics and cognitive science, as well as the design of computational systems to solve engineering problems in natural language processing (NLP). The course will combine analysis and discussion of these approaches with training in the programming and mathematical foundations necessary to put these methods into practice. The course is designed to accommodate students both with and without prior programming experience. Our goal is for all students to leave the course able to engage with and critically evaluate research in cognitive/linguistic modeling and NLP, and to be able to implement intermediate-level computational models for novel computational linguistics research.
Winter 2026 - LING 21730, LING 31730
Course Summary:
When hearing speech, humans rapidly and robustly map from a continuous acoustic signal to an abstract representation of the sounds of their language. This class will explore models of this acoustic-phonetic perceptual mapping by drawing from a variety of methodologies and perspectives. We will discuss the merits and issues of linguistic, computational, and neuroscientific approaches and draw connections between these disciplines. A background in neuroscience or computational modeling is not required.
Autumn 2025 - LING 22500, LING 32500, COGS 20027, DATA 20027
Course Summary:
This course provides an introduction to how quantitative methods are used in the analysis of linguistic data. This will include a foundation in statistical methods that can be applied to experimental and psycholinguistic data, including probability theory, hypothesis testing, regression models and the use of Bayesian statistics. Further topics will include a brief introduction to the use of basic machine learning algorithms in linguistic research and techniques that can be used in the analysis of large linguistic datasets. The class will be grounded in case studies from a variety of subfields of linguistics and provide hands-on examples through a guided introduction to programming. This class is intended for students who are interested in jump-starting a path into linguistic data science and is designed to be accessible to those with no experience in data science or programming.
Spring 2026
Spring 2026
Perceptual Models Of Speech [Schedule] [Syllabus]
Fall 2021
When hearing speech, humans rapidly and robustly map from a continuous acoustic signal to an abstract representation of the sounds of their language. This seminar will explore models of this acoustic-phonetic perceptual mapping by drawing from a variety of methodologies and perspectives. We will discuss the merits and issues of linguistic, computational, and neuroscientific approaches and draw connections between these disciplines. A background in neuroscience or computational modeling is not required.
Phonology I, Fall 2019, Fall 2020, Spring 2021: Teaching Assistant. Instructor: Dr. Peggy Antonisse.
Introductory Linguistics, Spring 2020: Teaching Assistant/Discussion Section Leader. Instructor: Dr. Tonia Bleam.
PULSAR Undergraduate Research Seminar, Spring 2022, Fall 2022: Graduate Mentor. Instructors: Tess Wood, Andrea Zukowski
Language at the Museum: Engaging the Public in Language Science, Summer 2022 Graduate Mentor/Assistant. Instructor: Charlotte Vaughn