The newest application of linguistics combines the power of machine learning and human language together to create the field of computational linguistics. This emerging branch holds much promise, as it can be applied to a variety of contexts and revolutionize work within other subfields of linguistics.
Computational linguistics is the study of methods that leverage computers’ enormous calculating power to recognize and generate patterns in language. The field emerged in the 1950s as machine translation, with the United States military funding attempts to develop programs meant to automatically translate Russian text into English. The results were a series of complex, hand-written rules the computer followed to generate a translation. Although such efforts were a limited success, these overtures signaled burgeoning interest in computational methods in linguistics.
Advancements in computational linguistics continued, with perhaps the greatest advancement in the field being the introduction of probabilistic and statistical methods. Faster computers and improved stochastic algorithms, as well as the compilation of enormous data sets on which programs could be trained, expanded the role of the computer; where computers had previously applied explicit rules provided by a programmer, they could now utilize inductive reasoning to detect and identify grammatical structures for themselves.
This use of computers to identify structures in natural language is known as natural language processing (NLP). NLP has a wide scope and application, ranging from determining whether an online product’s review is negative or positive (sentiment analysis) to interpreting a verbal command given to an app on your cell phone (speech recognition) and beyond. In fact, the term “computational linguistics” is largely synonymous with “natural language processing,” although the former is more often used to indicate methods in research to advance linguistic theory and the latter research for applications. The use of computers to generate language is known as natural language generation (NLG).
The field of computational linguistics has provided tools for incredible advancements in both theory and applications in various fields, and its growth does not appear likely to stop any time soon. In 2019, UF Linguistics hired Dr. Kevin Tang, who now offers a computational linguistics course in addition to conducting his own research. Hoping to emerge as a leader in this field, UF Linguistics is currently looking to hire another faculty member with a specialization in computational language science. If you are interested in learning more, we encourage you to watch our department’s recent presentation about computation linguistics.