The human language technology and computational linguistics immersion provides exposure to computational linguistics and relevant language science course work. Students gain knowledge and practical skills in computational natural language processing and technical linguistic analysis, useful for analytics and modeling with language data and for developing, evaluating, and maintaining language technology software.
This course provides theoretical foundation as well as hands-on (lab-style) practice in computational approaches for processing natural language text. The course will have relevance to various disciplines in the humanities, sciences, computational, and technical fields. We will discuss problems that involve different components of the language system (such as meaning in context and linguistic structures). Students will additionally collaborate in teams on modeling and implementing natural language processing and digital text solutions. Students will program in Python and use a variety of relevant tools. Expected: Programming skills, demonstrated via course work or instruction approval.
Choose two of the following:
Introduction to Language Science
This course introduces the basic concepts of linguistics, which is the scientific
study of human languages. Students will be introduced to core linguistic disciplines (phonetics, phonology, morphology, syntax, semantics, and pragmatics) and to principles of linguistics through discussion and the analysis of a wide range of linguistic data based on current linguistic models. English will often serve as the reference language, but we will discuss a wide variety of languages, including sign languages, to illustrate core concepts in linguistics. The course will have relevance to other disciplines in the humanities, sciences, and technical fields. Students will be encouraged to develop critical thinking regarding the study of human languages through discussions of the origins of languages, how languages are acquired, their organization in the brain, and languages' socio-cultural roles. Some other topics that will be introduced are: language globalization and language endangerment, language and computers, and forensic linguistics.
We will explore the relationship between language and technology from the
invention of writing systems to current natural language and speech
technologies. Topics include script decipherment, machine translation,
automatic speech recognition and generation, dialog systems, computational
natural language understanding and inference, as well as language
technologies that support users with language disabilities. We will also trace
how science and technology are shaping language, discuss relevant artificial
intelligence concepts, and examine the ethical implications of advances in
language processing by computers. Students will have the opportunity to
experience text analysis with relevant tools. This is an interdisciplinary
course and technical background is not required.
Science & Analytics of Speech
This course introduces students to the fields of experimental phonetics, the scientific study of the sounds used in human speech, and speech processing, the study of the speech signal used in automatic speech recognition, spoken emotion detection, and other technologies. Students will learn about the physiology of speech production and perception, and they will acquire the skills necessary to accurately describe speech concepts and to analyze speech using relevant methods and tools. Turning to speech processing technology, students will explore automatic speech recognition, speech synthesis, speaker identification, and emotion recognition, and learn how our understanding of human speech production and perception informs these technologies. The course will have relevance to other disciplines in the humanities, sciences, and technical fields. This course provides theoretical foundation as well as hands-on laboratory practice.
Seminar in Computational Linguistics
Study of a focus area of increased complexity in computational linguistics. The focus varies each semester. Students will develop skills in computational linguistics analysis in a laboratory setting, according to professional standards. A research project plays a central role in the course. Students will engage with relevant research literature, research design and methodology, project development, and reporting in various formats.