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. If there are answers to our questions that have already been discovered, we need artificial intelligence to 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. If there are answers to our questions that have already been discovered, we need artificial intelligence to find them.
Computational Linguists develop computer systems that deal with human language. They need a good understanding of both programming and linguistics.
This is a challenging and technical field, but skilled computational Linguists are in demand and highly paid. Computational Linguists 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, and many others.
Featured Computational Linguist
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.
How The Tracks Work
All Linguistics majors are required to take 4 courses (Introduction to Linguistics, Sound Structures, Semantics, and Morphology and Syntax). There's an additional requirement of five credit hours in a langauge 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 For Linguistics
Introduction to Programming & Problem Solving
Computational Reasoning 2: Representations of Data
Principles of Programming Languages
AI & Machine Learning
Machine Learning and Linguistics
Introduction to Data Science
Introduction to AI
Introduction to Machine Learning
Natural Language Processing
Introduction to Computational Linguistics
Computational Corpus Linguistics
Natural Language Processing
Conversation Analysis & Interactional Linguistics
Undergraduate Program Oppurtunities
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 Masters in Computer Science.
Minor in Information Science
The track includes several courses for the Information Science Minor. Finishing the minor will prepare you for positions in data analytics and information processing in 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 roles in: medical analysis, education and multimedia.
CLEAR (The Center for Computational Language and Education Research)
As a student, much of your work outside of the classroom will be conducted within CLEAR, a center dedicated to advancing Natural Language Processing 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. Here you can learn about CU’s NLP philosophy, peruse featured NLP projects, and find the reasources you’re looking for.
- The Major in Detail
- The Minor in Detail
- 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)