Ling 2000(or 2000H): Introduction to Linguistics

This course examines language as a system of human communication. It also provides students with the tools needed for the recording, investigation, and close analysis of language. The course consists of a general survey of language and linguistics. A number of topics relating to man’s knowledge and use of language are systematically investigated. Examples are drawn primarily from the English language, although other languages are used to illustrate certain concepts. Nevertheless, the focus of the course is not on any specific language or languages; rather, it is on properties common to all languages and on ways in which languages may differ. 3 credit hours. Prerequisites: None


Ling 2001: Language and Formal Reasoning

The goal of this course is to lead students to think analytically about syntax, meaning, and reasoning in terms abstract enough to encompass both natural languages (like English) and artificial formal languages (in this case, first-order logic) to see underlying structural similarities and to understand some fundamental differences as well. This goal is accomplished by (1) introducing students to two kinds of formal systems, first-order logic and formal phrase-structure grammars, (2) using these systems to analyze syntax and reasoning, in symbolic form and in English, and (3) examining differences between artificial and natural language in principles of cooperative communication. 3 credit hours. Prerequisites: Math 1075 or equivalent, or Math placement level R


Ling 2051(or 2051H): Analyzing the Sounds of Language

In this course, we will introduce pertinent ideas and results from research in the various disciplines that have contributed to our understanding of the sounds of language. We will introduce some of the quantitative analytical tools that are used in the phonetic sciences, and do several experiments in class, to give a flavor of the diverse research methods that speech scientists have developed to try to determine how speech is produced and perceived by humans. 3 credit hours. Prerequisites: Math 1075 or equivalent, or Math placement level R


Ling 3801: Code Making and Code Breaking

This course has two main aims. It introduces old and new technologies for code making and code breaking, and it shows how good and bad choices in how codes are used can affect whether they succeed or fail. Students will learn what codes are, how they work and how they are used. The topics discussed will include code breaking, digital signatures, quantum cryptography and the decipherment of ancient languages. 3 credit hours. Prerequisites: None


Ling 3802(or 3802H): Language and Computers

This is an introduction to human language technology. In this subject area we study whether and how it is possible for humans and computers to communicate in ordinary language. The widening use of computers has had a profound influence on the way ordinary people communicate, search and store information. For the overwhelming majority of people and situations, the main vehicle for such information is human language. Text and speech are crucial encoding formats for the information revolution. This course will give students insight into the fundamentals of how computers are used to represent, process and organize textual and spoken information, as well as provide tips on how to effectively integrate this knowledge into their work. The course will cover the theory and practice of human language technology. Topics include text encoding, search technology, tools for writing support, machine translation, dialog systems, computer aided language learning and the social context of language technology. 3 credit hours. Prerequisites: Not open to students with first-year standing


Ling 3803: Ethics of Language Technology

Rapid increases in the capabilities of Natural Language Processing (NLP) systems and other language technologies are leading us toward a world in which computers make many of the decisions which affect our everyday lives. NLP systems are already involved in hiring workers, filtering our words online and deciding how political campaigns choose to approach us. These systems have immense power--- but all too often, they make unfair decisions that reflect or even amplify the biases of the society that created them. In this course, we'll learn about how language processing systems are created, and at what steps in the process bias and unfairness might creep in. We'll learn about efforts to define, detect and quantify bias, and how different ethical principles can lead to different results. Finally, we will discuss different ways to remedy the ethical problems of language technology, to what extent they can be 'fixed', and whether there are problems for which it is too dangerous to use NLP at all. 3 credit hours. Prerequisites: None


Ling 4100: Phonetics

Cross-linguistic survey of the sounds of the world's languages. 3 credit hours. Prerequisites: Ling 2000, 2000H, or 5000


Ling 4200: Syntax

Basic elements of syntactic description and an overview of syntactic structure across languages. 3 credit hours. Prerequisites: Ling 2000, 2000H, or 5000


Ling 4300: Phonology

Introduction to phonological analysis and description, and an overview of phonological structure across languages. 3 credit hours. Prerequisites: Ling 2000, 2000H, or 5000


Ling 4350: Morphology

The grammatical analysis of words, and an overview of morphological structure across languages. 3 credit hours. Prerequisites: Ling 2000, 2000H, or 5000


Ling 4400: Linguistic Meaning

Introduction to linguistic meaning across languages, including word meaning, the contribution of syntactic structure, and the role of context in interpretation. 3 credit hours. Prerequisites: Ling 2000, 2000H, or 5000


Ling 5050: Technical Tools for Linguists

Practical training in standard computational tools for tackling different kinds of linguistic research. Students will learn computational techniques to access, search and format linguistic datasets, including text corpora, speech and audio, structured representations such as parse trees, and experimental measurements. The course will also cover data exploration and basic modeling. 3 credit hours. Prerequisites: None


Ling 5801: Computational Linguistics 1

Symbolic computation applied to the structure of words and sentences, models of morphology and syntax, parsing algorithms. 3 credit hours. Prerequisites: Ling 3802, Ling 5000, CSE 3321, CSE 3522, or CSE 5052; or permission of instructor


Ling 5802: Computational Linguistics 2

Computational models of semantic interpretation, and the role of pragmatic knowledge in sentence processing; implementation of current grammatical theories. 3 credit hours. Prerequisites: Ling 5401 and Ling 5801


Ling 5803: Computational Semantics

Methods for construction semantic representations for fragments of natural language and performing inference with such representations. 3 credit hours. Prerequisites: Ling 5801


English/Ling 5804: Analyzing Language in Social Media

Course gives students experience analyzing language in social media. It covers theoretical issues arising in digital communication and provides hands-on practice at computational data analysis, applicable across fields. Students gain an understanding of the sociolinguistic dynamics of online communication and the technical skills to conduct research on them. No previous experience in linguistics or programming is required, though some background in the study of language will be helpful.

Team taught. 3 credit hours. Prerequisites: None


English 3721: Structure of the English Language

Students learn basic characteristics of English linguistics focusing on the basic building blocks of language; the sounds of English and how they are put together, word formation processes, and rules for combining words into utterances/sentences. Students investigate and explore linguistic variation, accents of American English, and the implications of language evaluation in educational settings. 3 credit hours. Prerequisite: English 1110.01


Computer Science & Engineering, CSE 3521: Survey of Artificial Intelligence 1

Survey of basic concepts and techniques in artificial intelligence, including problem solving, knowledge representation, and machine learning. 3 credit hours. Prerequisites: CSE 2331 or 5331, and enrollment in CSE, CIS, ECE, or Data Analytics major.


Computer Science & Engineering, CSE 5525: Foundations of Speech and Language Processing

Fundamentals of natural language processing, automatic speech recognition and speech synthesis; lab projects concentrating on building systems to process written and/or spoken language. 3 credit hours. Prerequisites: CSE 3521 or 5521; and CSE 5522, Stat 3460, or Stat 3470.