31 - 40 of 129 results for: LINGUIST

The diversity of human languages, their sound systems, vocabularies, and grammars. Tracing historical relationships between languages and language families. Parallels with genetic evolutionary theory. Language policy, endangered languages and heritage languages. Classification of sign languages.

This course covers the foundations of the linguistic subfield concerned with comparing and classifying world languages. The course provides an overview of the analytic tools which may be used to identify and classify a language based on its phonological, morphological, and syntactic properties, and explores the major ways in which languages may be similar or different in these domains. Students will acquire a useful toolkit for studying novel, unusual, and typologically diverse linguistic data, and for conducting fieldwork on understudied languages. Prerequisites: Linguist 110, 121A, 121B, 130A, 130B, or permission of the instructor.

This course examines constructed languages, which are languages that were invented rather than arising naturally. We will cover the components that characterize a language, including phonetics, phonology, morphology, syntax, and writing systems. These characteristics vary among languages of the world, so constructing a language involves many decisions about each of these characteristics. Using the tools of linguistic theory, we will analyze examples of constructed languages, both those from fiction (e.g. Klingon, High Valyrian, Sindarin) and those intended for real-world usage (e.g. Esperanto). Students will each construct their own language based on the concepts we discuss.

NLP for extracting meaning from text and social networks on the web, and interacting with people via language. Introducing methods (from regex to large language models, via logistic regression, gradient descent, transformers and other neural networks, social networks, collaborative filtering), applications (chatbots, information retrieval, social computing, recommender systems), and ethical and social issues. Prerequisites: CS106B, Python (at the level of CS106A), CS109 (or equivalent background in probability), and programming maturity and knowledge of UNIX equivalent to CS107 (or taking CS107 or CS1U concurrently).

Project-oriented class focused on developing systems and algorithms for robust machine understanding of human language. Draws on theoretical concepts from linguistics, natural language processing, and machine learning. Topics include lexical semantics, distributed representations of meaning, relation extraction, semantic parsing, sentiment analysis, and dialogue agents, with special lectures on developing projects, presenting research results, and making connections with industry. Prerequisites: CS 224N or CS 224S (This is a smaller number of courses than previously.)

Performance with language (speaking, reading, writing, listening, translating or interpreting) is used to measure a person's proficiency or achievement level in the language. Language performance is also used to measure other human characteristics, including psycho-social states and traits. The course will review basic methods in language measurement and cover their use as applied in education, psychology, and commerce. Topics include both traditional and automatic methods for assessing speaking, reading, writing, affect, and language disorders. Students will develop, apply, and evaluate a language test.

Designed for undergraduates beginning or working on research projects in linguistics. Participants present and receive feedback on their projects and receive tips on the research and writing process.

Introduction to linguistic research via presentations by Stanford linguistics faculty and graduate students. Open to undergraduate students interested in linguistics. Required for linguistics majors.

Senior capstone seminar. Joint readings in an annually varying topic, exploring the implications and importance of linguistic research for other domains of knowledge or practice.