Courses

Ling 571: Computational Corpus Linguistics (Fall 2006) — by Rob Malouf — last modified 2006-11-14 10:38

Advances in technology have revolutionized the way linguists approach their data. Using computers, extremely large bodies of text ("corpora") can be collected and analyzed at a level of detail that only a generation ago would have been unthinkable. For linguists and computer scientists alike, the accelerating growth of the World Wide Web and other natural language resources have made techniques for dealing with very large texts more important than ever. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for computer-aided text manipulation. Students will learn to construct and search text databases using Unix tools, to write python programs to manipulate large natural language corpora, and to use statistical software to perform quantitative analysis of linguistic data.

Ling 681: Statistical Methods in Natural Language Processing (Fall 2006) — by Rob Malouf — last modified 2006-11-14 10:38

This course offers an introduction to statistical methods in computational linguistics. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for evaluating constructing statistical natural language processing applications and for evaluating their results. Topics to be covered include: basic probability and information theory, statistics for corpus analysis and hypothesis testing, Markov chains and sequence models, probabilistic context-free grammars, stochastic attribute value grammars, and machine learning algorithms.

Ling 795: Analyzing Web Texts (Spring 2006) — by Rob Malouf — last modified 2006-11-14 10:38

Web text, such as blogs, newsgroups, message boards, and email lists, can provide an easily collected and incredibly rich source of data on a nearly limitless range of topics. However, the sheer quantity of data makes comprehensive qualitative analysis impossible, and the nature of web texts present a set of unique challenges for standard computational methods. In this seminar, we will investigate web texts as a distinct text type (or types), looking at the linguistic and extra-linguistic properties that make them unique. We will also explore some of the data-intensive methods that can be used to extract useful information from large, noisy collections of web texts.

Ling 570: Mathematical Linguistics (Fall 2006) — by Rob Malouf — last modified 2006-11-14 10:38

This course serves as an introduction to various mathematical tools used by linguists in analyzing language and in constructing a formal description of a language. The course covers tools that have been used for both natural and artifical languages. The course assumes no mathematical background and so begins by surveying two mathematical areas.

Ling 522: Introduction to Syntax (Fall 2006) — by Rob Malouf — last modified 2006-11-14 10:38

This course will serve as an introduction to the field of syntax, focusing on the Principles and Parameters framework and concluding with a brief introduction to Minimalism.

Ling 582: Computational Syntax and Semantics (Fall 2006) — by Rob Malouf — last modified 2006-11-14 10:38

Syntactic and semantic processing is at the heart of many NLP applications, classically with the aim of producing a representation of the meaning of a sentence, although a recent trend in the field has been the increasing importance of more shallow forms of syntactic analysis.

Ling 354: Language and Computers (Spring 2007) — by Rob Malouf — last modified 2008-05-01 14:16

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 520: Fundamentals of Linguistics (Spring 2007) — by Rob Malouf — last modified 2008-05-01 14:16

Principles of modern linguistics, with attention to English grammar (syntax, morphology, phonology). Language change, dialects, sociolinguistics, psycholinguistics, language acquisition.

Ling 620: Advanced Formal Syntax (Spring 2007) — by Rob Malouf — last modified 2007-01-24 11:08

Advanced study of formal syntactic theory.

Ling 354: Language and Computers (Fall 2006) — by Rob Malouf — last modified 2006-08-28 10:14

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 354: Language and Computers (Spring 2006) — by Rob Malouf — last modified 2006-11-14 10:38

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 571: Computational Corpus Linguistics (Fall 2007) — by Rob Malouf — last modified 2008-05-01 14:13

Advances in technology have revolutionized the way linguists approach their data. Using computers, extremely large bodies of text ("corpora") can be collected and analyzed at a level of detail that only a generation ago would have been unthinkable. For linguists and computer scientists alike, the accelerating growth of the World Wide Web and other natural language resources have made techniques for dealing with very large texts more important than ever. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for computer-aided text manipulation. Students will learn to construct and search text databases using Unix tools, to write python programs to manipulate large natural language corpora, and to use statistical software to perform quantitative analysis of linguistic data.

Ling 795: Dependency Parsing (Fall 2007) — by Rob Malouf — last modified 2008-05-01 14:14

In recent years, dependency parsing has emerged as a serious alternative to traditional phrase structure grammar analysis. In this seminar, we will review the literature on dependency parsing, both for hand-constructed grammars and treebank grammars, and on the applications of dependency formalisms in natural language processing.

Ling 354: Language and Computers (Fall 2007) — by Rob Malouf — last modified 2008-05-01 14:18

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 354: Language and Computers (Spring 2008) — by Rob Malouf — last modified 2008-05-01 14:18

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 581: Computational Linguistics (Spring 2008) — by Rob Malouf — last modified 2008-05-01 14:18

This course will serve as an introduction to the field of computational linguistics. The course begins with an introduction to finite-state automata and some basic natural language applications; this is extended to finite-state transducers with applications in phonology and morphology. Other topics covered: basic concepts of speech processing, the Viterbi algorithm, ngram language models, part of speech tagging, context-free grammars and context-free parsing, and information retrieval.

Ling 523: Morphology (Spring 2008) — by Rob Malouf — last modified 2008-05-01 14:19

This course offers an introduction to the theoretical principles of word structure. Topics to be covered include inflection, derivation, and compounding; the organization of the lexicon; the structure of inflectional paradigms; morphophonological and morphosyntactic alternations; and computational applications. After successful completion of this course, students will be able to describe and analyze the structure of words and recognize different types of word structure, to apply current theories of word structure to new examples, and to recognize the role of morphological data for the construction of linguistic theory.

Ling 354: Language and Computers (Fall 2008) — by Rob Malouf — last modified 2008-09-05 09:31

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 571: Computational Corpus Linguistics (Fall 2008) — by Rob Malouf — last modified 2008-09-05 10:35

Advances in technology have revolutionized the way linguists approach their data. Using computers, extremely large bodies of text ("corpora") can be collected and analyzed at a level of detail that only a generation ago would have been unthinkable. For linguists and computer scientists alike, the accelerating growth of the World Wide Web and other natural language resources have made techniques for dealing with very large texts more important than ever. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for computer-aided text manipulation. Students will learn to construct and search text databases using Unix tools, to write python programs to manipulate large natural language corpora, and to use statistical software to perform quantitative analysis of linguistic data.

Ling 681: Statistical Methods in Natural Language Processing (Fall 2008) — by Rob Malouf — last modified 2008-09-09 10:11

This course offers an introduction to statistical methods in computational linguistics. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for evaluating constructing statistical natural language processing applications and for evaluating their results. Topics to be covered include: basic probability and information theory, statistics for corpus analysis and hypothesis testing, Markov chains and sequence models, probabilistic context-free grammars, stochastic attribute value grammars, and machine learning algorithms.

Ling 354: Language and Computers (Spring 2009) — by Rob Malouf — last modified 2009-01-26 11:17

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 520: Fundamentals of Linguistics (Spring 2009) — by Rob Malouf — last modified 2009-01-26 11:19

Principles of modern linguistics, with attention to English grammar (syntax, morphology, phonology). Language change, dialects, sociolinguistics, psycholinguistics, language acquisition.

Ling 795: Simulation in Linguistics (Spring 2009) — by Rob Malouf — last modified 2009-03-19 14:20

Since 1957, the primary goal of theoretical linguistics has been to discover the details of Universal Grammar, the principles which underly all human languages as a reflection of our innate language faculty. More recent work in linguistics has explored alternate sources of explanation for cross-linguistic generalizations, appealing to usage patterns, diachronic factors, and even random chance. In this approach, the current state of any language is a snapshot in an on-going gradual development over many generations, and constraints on the way in which languages evolve are one possible source of similarities across languages. Unfortunately, the time depth of linguistic change makes it impossible to directly test hypotheses regarding evolutionary explanations. Linguistics is, of course, not alone in facing this challenge. In many fields, practical and ethical constraints make it impossible to test theoretical claims via controlled laboratory experiments. As in fields like biology, economics, and chemistry, predictions about the dynamics of language evolution can be tested via computer simulation. In this seminar, we will review the literature on simulation, both in linguistics and in related fields, and explore how this view of language as a complex dynamic system relates to current developments in linguistic theory. Topics which may covered include: agent-based and evolutionary simulation, exemplar-based models, the origins of language, Monte Carlo methods in statistics, and language as a complex adaptive system. The final content of the course will depend on the interests of the participants.

Ling 354: Language and Computers (Fall 2009) — by Rob Malouf — last modified 2009-09-11 09:35

This course offers an introduction and overview of natural language processing and computational linguistics. Topics to be covered include speech recognition and generation, spelling and grammar checkers, information retrieval and search engines, conversational agents, and machine translation.

Ling 523: Morphology (Fall 2009) — by Rob Malouf — last modified 2009-09-11 09:37

This course offers an introduction to the theoretical principles of word structure. Topics to be covered include inflection, derivation, and compounding; the organization of the lexicon; the structure of inflectional paradigms; morphophonological and morphosyntactic alternations; and computational applications. After successful completion of this course, students will be able to describe and analyze the structure of words and recognize different types of word structure, to apply current theories of word structure to new examples, and to recognize the role of morphological data for the construction of linguistic theory.

Ling 571: Computational Corpus Linguistics (Fall 2009) — by Rob Malouf — last modified 2009-09-11 09:38

Advances in technology have revolutionized the way linguists approach their data. Using computers, extremely large bodies of text ("corpora") can be collected and analyzed at a level of detail that only a generation ago would have been unthinkable. For linguists and computer scientists alike, the accelerating growth of the World Wide Web and other natural language resources have made techniques for dealing with very large texts more important than ever. Through a combination of lectures, demonstrations, and hands-on exercises, this course will give students an introduction to the skills necessary for computer-aided text manipulation. Students will learn to construct and search text databases using Unix tools, to write python programs to manipulate large natural language corpora, and to use statistical software to perform quantitative analysis of linguistic data.