71 - 80 of 129 results for: LINGUIST

How can we understand natural language use in computational terms? This course surveys probabilistic models for natural language semantics and pragmatics. It begins with an introduction to the Rational Speech Acts framework for modeling pragmatics as social reasoning. It then explores a variety of phenomena in language meaning and usage. Probabilistic programming will be used as a precise and practical way to express models.

This course offers practical training in conducting and presenting scientific research in phonetics, developmental psycholinguistics, and the intersection of linguistics with clinical fields for the study of child speech and language development. Students workshop ongoing research, provide peer feedback on scientific writing, discuss current literature, and gain hands-on experience with research methods for studying language development in infants and children. The course emphasizes methodological approaches across diverse research contexts, from controlled laboratory experiments to naturalistic language sampling.

Are bilinguals merely the combination of two monolinguals? Do bilinguals think differently in each language? How do bilinguals manage the complexity of two languages in their minds and daily interactions? This course offers a theoretical exploration of bilingualism and second language acquisition through a psycholinguistic lens. Topics covered include heritage and second language acquisition, language comprehension and production, speech perception, language attrition, code-switching, and cognitive and neurolinguistic development. Through lecture discussions and hands-on analysis, students will gain a deeper understanding of the intricacies of bilingual language use and its psychological underpinnings. Prerequisites: Linguist 1, Linguist 105/205, Linguist 110, Linguist 121A/121B, Linguist 145/245

Human language is one of the most remarkable phenomena in nature. Unlike all other known forms of animal communication, language allows us to transmit virtually any kind of mental content: personal memories, ancient history, cultural traditions, imaginary worlds, complex plans, religious beliefs, mathematical proofs, moral norms, and explanations of ourselves and the universe we inhabit. The existence of language raises profound questions about the human mind and brain. What do we know when we know a language? How do we translate pressure waves in air into ideas, and vice versa? How can such a complex system be learned so quickly and universally by children? What's special about our brains that enables this to happen? What's the relationship of language to our broader capacities for thinking and social interaction? This course will introduce you to the ongoing scientific project to tackle these kinds of questions. You will both (1) become familiar with major psycholinguistic research questions and results, and (2) hone your scientific thinking about language and the human mind, developing skills necessary to identify both predictions made by psycholinguistic theories and experimental strategies for testing those predictions.

Over the past 20 years, linguists have become increasingly interested in testing theories with a wider range of empirical data than the traditionally accepted introspective judgments of hand-selected linguistic examples. Consequently, linguistics has seen a surge of interest in psycholinguistic methods across all subfields. This course will provide an overview of various standard psycholinguistic techniques and measures, including offline judgments (e.g., binary categorization tasks like truth-value judgments, Likert scale ratings, continuous slider ratings), response times, reading times, and eye-tracking. Students will present and discuss research articles, but the bulk of the course is project-based: students will run an experiment (either a replication or an original design, if conducive to the student's research) to gain hands-on experience with experimental design and web-based experimentation; data management, analysis, and visualization in R; and open science tools like git/GitHub and pre-registration.

Adaptation to speaker variability in language use has receivednincreasing attention in recent years from linguists and psychologistsnalike, who have recognized that, though long ignored, it poses a problemnfor static theories of language. The course will present a broad surveynof recent work in this area across levels of linguistic representation,nincluding phonetic, lexical, syntactic, prosodic, and semanto-pragmaticnadaptation. We will discuss the cognitive underpinnings of adaptationnand its relation to priming and learning, compare adaptation in varyingndomains, and consider the implications for theories of language andncommunication. The course will be organized primarily around discussionnof assigned readings. Students will develop a research proposal relevantnto issues in adaptation. May be repeated for credit. Prerequisite: LINGUIST 145 or background in any subfield of linguistics

Regular meetings of members of the Alps Lab.

What are the neural representations and computations that give humans the amazing and unique ability to use language? This seminar course provides an overview of the field of cognitive neuroscience of language, examining the landmark empirical discoveries that have shaped our understanding of language comprehension and production in the brain. Lectures cover all aspects of language processing, from early sensory perception, to recognizing individual words, to processing complex to higher level semantic and syntactic structures. We will discuss findings from different neuroimaging methods, as well as insight from individuals with language processing disorders.

This course provides hands-on practical training in the process and presentation of scientific research in computational linguistics, psycholinguistics, and language neuroscience. Students present and provide feedback on their ongoing research, workshop in-progress research ideas, peer review each other's scientific writing, present and discuss published work in the field, and receive tutorial training in computational and statistical methods.