Breadcrumb
More language has been recorded in the last twenty years than in the entirety of human history. Using computer science algorithms, Computational Linguists can automatically process vast amounts of written and spoken communication in mere moments. This is the mechanism that turns the chaos of billions of individual voices into the symphony that is our civilization. Computational Linguistics is an attempt to manufacture the keys to a library containing the sum total of human knowledge and experience. Many of the answers to our questions already exist; we need artificial intelligence to help us find them.
More language has been recorded in the last twenty years than in the entirety of human history.
Computational Linguists use computer science algorithms to automatically process vast amounts of written and spoken communication in moments. This is the mechanism that turns the chaos of billions of individual voices into the symphony that is our civilization.
Computational Linguistics is an attempt to manufacture the keys to a library containing the sum total of human knowledge and experience. Many of the answers to our questions already exist; we just need artificial intelligence to help us find them.
Companies
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.
Featured Computational Linguist
Sarah Moeller
Linguistics is a great tool to address issues we all personally care about, but by far the greatest impact can be had by leveraging computers to help us get the data we all need to do proper linguistic analysis. We can also automate some linguistic tasks to make up for limited exposure and interest in solving the issues of smaller, marginalized communities.
Computational Linguistics
CU is unique in having students on the Computational Linguistics track undertake study in Computer Science and Linguistics in equal amounts. Computer science algorithms are needed to model language as a process, but optimal performance can only be achieved through understanding the nuances of language.
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.
The track also serves as a certification in this discipline and the student's transcript will reflect this.
Computational Track Courses
Core Courses & Electives
Programming
Core Courses
LING 1200
Programming For Linguistics
Electives
CSCI 2207
Introduction to Programming & Problem Solving
INFO 2201
Computational Reasoning 2: Representations of Data
CSCI 3155
Principles of Programming Languages
AI & Machine Learning
Core Courses
LING 4632
Machine Learning and Linguistics
Electives
CSCI 3022
Introduction to Data Science
CSCI 3202
Introduction to AI
CSCI 4622
Introduction to Machine Learning
Natural Language Processing
Core Courses
LING 3822
Introduction to Computational Linguistics
LING 4200
Computational Corpus Linguistics
Electives
CSCI 3832
Natural Language Processing
LING 4700
Conversation Analysis & Interactional Linguistics
Undergraduate Program Opportunities
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.
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.
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.
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 toles in medical analysis, education, and multimedia.
CLEAR (The Center for Computational Language and Education Research)
Much of a CLASIC student's work outside of the classroom will be conducted within CLEAR, a center dedicated to advancing Natural Language Processing, and which houses many government funded research projects. The facilities include labs, meeting rooms, graduate student offices, and computing resources.
Natural Language Processing @ CU
The Natural Language processing hub at CU allows students to learn about CU’s NLP philosophy, peruse featured NLP projects, and find beneficial resources.
Resources
- The Major in Detail
- The Minor in Detail
- Advising
- The Four-Year Plan
- Linguistics Major Tracks
- Bachelor's - Accelerated Master's Program
- LURA Awards and Research Blogs
- Mentored Research Opportunities
- Honors Program
- Certificate Programs
- Education Abroad
- Independent Study
- The Literacy Practicum
- Undergraduate Research Opportunities (UROP)
