Dr. Hulden's research focuses on modeling and automatically learning phenomena in natural language morphology and phonology. Much of this work is informed by results in information theory, machine learning, including neural networks, and theoretical computer science.
keywords
computational linguistics, computational phonology and morphology, grammatical inference, formal language theory, learnability, machine learning, natural language processing for less-resourced languages, historical linguistics
CSCI 5832 - Natural Language Processing
Primary Instructor
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Spring 2018 / Spring 2019
Explores the field of natural language processing as it is concerned with the theoretical and practical issues that arise in getting computers to perform useful and interesting tasks with natural language. Covers the problems of understanding complex language phenomena and building practical programs. Same as LING 5832.
CSCI 7565 - Computational Phonology and Morphology
Primary Instructor
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Spring 2020
Surveys of the main approaches and central questions related to computational modeling and learning of morphology and phonology. We consider questions related to learnability of phonology/morphology, machine learning implementations, and linguist-driven grammar modeling.
LING 1200 - Programming for Linguistics
Primary Instructor
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Fall 2019 / Fall 2021
Presents techniques for computer programming in high level programming languages such as Python to address a range of problems with a specific focus on language processing and linguistics. The class is suitable for students with little to no prior experience in computing or programming. Degree credit not granted for this course and CSCI 1200 or INFO 1201. Recommended prerequisite: LING 2000.
LING 4100 - Perspectives on Language
Primary Instructor
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Fall 2019
Provides extended critical examination of a few selected issues, chosen each term for their general interest and relevance, e.g., the relation between language and thought, or human language vs. animal languages, and computer languages. May be repeated up to 9 total credit hours, provided topics vary. Recommended prerequisite: LING 2000.
LING 4632 - Machine Learning and Linguistics
Primary Instructor
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Spring 2022
Is an introduction to machine learning, with a focus on linguistic applications. It is oriented toward students who want to understand the basics of machine learning and apply well-known techniques to address problems related to language and linguistics. The main goal is to achieve a practical grasp of the fundamental and most successful concepts in machine learning and to be equipped with techniques to apply this knowledge in linguistic domains. The course is also intended to provide a perspective on natural language acquisition and learning, namely, insight into what types of language acquisition problems are truly difficult, and what types of learning problems can be solved by fairly straightforward pattern recognition techniques. Formerly offered as a special topics course.
LING 5410 - Phonology
Primary Instructor
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Spring 2018 / Spring 2019 / Spring 2020 / Spring 2022
Studies sound systems of language. Introduces both principles of organization of sound systems and major kinds of phonological structures found worldwide. Provides extensive practice in applying phonological principles to data analysis. Recommended prerequisite: LING 5030.
LING 5832 - Natural Language Processing
Primary Instructor
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Spring 2018 / Spring 2019
Explores the field of natural language processing as it is concerned with the theoretical and practical issues that arise in getting computers to perform useful and interesting tasks with natural language. Covers the problems of understanding complex language phenomena and building practical programs. Same as CSCI 5832.
LING 6300 - Topics in Language Use
Primary Instructor
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Fall 2019 / Spring 2022
Discusses current issues and research in a selected area related to language use and function. Sample topics include conversational interaction, language policy, language content, and sociolinguistic variation.
LING 7565 - Computational Phonology and Morphology
Primary Instructor
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Spring 2020
Surveys of the main approaches and central questions related to computational modeling and learning of morphology and phonology. We consider questions related to learnability of phonology/morphology, machine learning implementations, and linguist-driven grammar modeling. Recommended prerequisites: LING 5410 and LING 5420.
LING 7800 - Open Topics in Linguistics
Primary Instructor
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Fall 2018
Various topics not normally covered in the curriculum; offered intermittently depending on student demand and availability of instructors. Contact the department office for information.
