Companies
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Computational Linguistics is a challenging and technical field that requires knowledge of both programming and linguistics. Skilled Computational Linguists are in demand and are highly paid to develop computer systems that deal with human language. Companies such as these below employ Computational Linguists to build systems that can perform tasks such as speech recognition (e.g., Siri), speech synthesis, machine translation (e.g., Google Translate), grammar checking, text mining and other "Big Data" applications.听
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Amazon
Roku
Rosetta Stone
Microsoft
Allen Institute
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Featured Computational Linguist
Sarah Moeller
Linguistics is a great tool to address issues听we all personally care about, but by far the greatest impact can be had by leveraging computers to help us get the data听we all need to do proper linguistic analysis.听We can also automate some linguistic tasks to make up for limited exposure and interest in solving the issues of smaller, marginalized communities.
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Computational Lingustics
CU is unique in its emphasis on having Computational Linguists study equal amounts of Computer Science and Linguistics. Computer science algorithms are needed to model language as a process, but optimal performance can only be achieved through understanding the nuances of language.
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How The Tracks Work
All Linguistics majors are required to take 4 courses (Introduction to Linguistics, Sound Structures, Semantics, and Morphology & Syntax). There's an additional requirement of five credit hours in a language other than English at the 3000 level or above. The four tracks are a formalization of the additional elective credit hour choices that will prepare students for employment or further education in a specific discipline of linguistics.听
The track also serves as a certification in this discipline and the student's transcript will reflect this.听
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The Computational Track Courses
Core Courses & Electives
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Programming
Core Courses
Programming For Linguistics
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Electives
Computer Science 2: Data Structures
Computational Reasoning听2: Representations听of Data
Principles听of听Programming听Languages
AI听& Machine听Learning
Core Courses
Machine Learning and Linguistics
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Electives
Introduction听to听Data听Science
Introduction听to听AI
Introduction听to Machine Learning
Natural Language听Processing
Core Courses
Computational Linguistics
Computational听Corpus Linguistics
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Electives
Natural Language听Processing
Conversation听Analysis听&听Interactional Linguistics
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Undergraduate Program Opportunities
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Minor in
Computer Science
The track includes several courses in the Computer Science Minor. Finishing the minor can better prepare you for jobs in telecommunications, information processing, and data retrieval, or put you on the road to a Master's in Computer Science.听
Minor in
Information Science
The track includes several courses for the Information Science Minor. Finishing the minor will better prepare you for positions in data analytics and information processing with an NLP bent.听
Minor in
Data Science
The track includes several courses for the Data Science Minor. Explicitly designed to complement many different majors, the minor provides a more focused path to positions in data analytics than an Information Science Minor.听
The Cognitive Science
Certificate
The Cognitive Science Certificate requires only three additional courses. The addition of a perspective from psychology will better prepare you for roles in medical analysis, education, and multimedia.听
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CLEAR (The Center for Computational Language and听Education听Research)
Much of a CLASIC student's work听outside of the classroom听will be听conducted within CLEAR,听a center dedicated to advancing Natural Language Processing, and which听houses many government funded research projects. The facilities include labs,听meeting rooms,听graduate student offices,听and computing resources.
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Natural Language听Processing听@听CU
The Natural Language processing hub at CU allows students to learn about CU鈥檚 NLP philosophy, peruse featured NLP projects, and find beneficial resources.听