Program type:


On Campus
Est. time to complete:

2 years
Credit Hours:

Research, develop, and perfect the technology to study languages and improve human-computer communications with a Master's in Computational Linguistics.
Computational technologies are increasingly present in daily life, from voice-enabled smartphone assistants to predictive text input to machine translation technologies. From an academic viewpoint, CL is the scientific study of language from a computational perspective, living at the intersection of language and technology. Students develop keen skills in linguistics and linguistic analysis. This knowledge can then be applied to the design of computational systems for automating linguistic analysis. At UNT we place a particular focus on how computational methods can support the work of documenting endangered languages, linking two of our department's strengths.

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Why earn a degree in Computational Linguistics Master's?

Computational Linguistics (CL) is a rapidly growing field in the high-tech sector, critical for the development of technologies such as voice-enabled smartphones (e.g. Siri, Cortana) and home assistants (e.g. Alexa). IBM’s Jeopardy-winning Watson system is another example of what CL can do.

Yet another application area is text analytics for market analysis. This concentration is specifically intended to address a growing need for language processing skills, particularly those associated with the rapid growth of artificial intelligence/cognitive technologies.

Systems like Siri or Alexa are built on a pipeline of language processing technologies, ranging from voice and speech recognition to language understanding and automatic question answering. Developing such technologies is a complex process that requires knowledge from both Linguistics and Computer Science.

This program will equip students with the research design and technology skills to apply their linguistics studies to real-world problems.

Why Earn a Computational Linguistics Master's?
  • Language structure analysis
  • Analyze language function and use
  • Analyze diverse populations' linguistic behaviors
  • Critical thinking
  • Formulate solutions to complex issues

Computational Linguistics Master's Highlights

Our strengths lie in our established TESOL program and research areas in language variation and change, language documentation, linguistic analysis of literature, language technology and language data curation. Our international collaborations currently are with Mexico, India, Pakistan and China.
UNT is one of a few Linguistics programs in the country to offer regular courses in the linguistic analysis of poetry and prose. The courses focus on the many kinds of repetition that are used by the world’s great writers, which have the effect of making literary texts a permanent part of the world’s art.
Students will get hands-on experience to develop technical skills in areas such as automatic linguistic analysis, machine learning, computer programming, and more.
Beginning full-time students who meet all qualifications may apply for financial assistance from the UNT office of Student Financial Aid and Scholarships. In addition, beginning and continuing students may apply for financial assistance from the Department of Linguistics.
Our program offers courses in professional development to help graduates with career placement.
UNT Linguistics is supported by an active linguistics research community at UNT with ties across campus and with local, national, and international communities.

What Can You Do With a Computational Linguistics Master's?

Graduates may work in the following areas:

  • Natural Language Processing
  • Computational Linguistics
  • Learning Technologies
  • Digital Data Curation
  • Business Analytics
  • Information Science

Computational Linguistics Master's Courses You Could Take

Computational Linguistics I (3 hrs)
Introduction to the computational analysis of language, focusing on core methods in natural language processing. Combination of theory and implementation (in Python).
Python Programming for Text (3 hrs)
Teaches Python programming focusing on applications for text.
Tools and Methods for Lexicography and Language Analysis (3 hrs)
Creation of language documentation outputs, dictionaries, text collections and language description using lexicographic tools and endangered language data. Includes the use of automated language annotation and acoustic analysis.
NLP in Linguistics (3 hrs)
Advanced course in text processing with Python focusing on the application of traditional machine learning methods and deep learning methods to NLP problems. Understand and apply DEEP LEARNING techniques to classical problems in NLP such as Text classification, Sequence labeling, and Machine Translation.
Corpus Linguistics (3 hrs)
Introduces computerized research methods, which are applied to large databases of language used in natural communicative settings to supplement more traditional ways of linguistic analysis in all linguistic sub-disciplines.
Research Design in Linguistics (3 hrs)
Provides an introduction to research methods in linguistics and applied linguistics/ESL with a focus on empirical research and the social and behavioral aspect of language science. Covers a range of techniques for conducting linguistic research including language data elicitation, data compilation, and data mining.

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