Computational linguistics is the study of language with the help of computers. This is a broad field which combines linguistics with computer science, and sometimes also involves other fields such as cognitive science and information science. Some goals of computational linguistics are the following.

To study language by exploring collections of digital language data (Corpus linguistics)
To make computer models that process language (Natural Language Processing, NLP)
To make applications that perform useful tasks, such as machine translation (Language Technologies)

The computer processing of language not only supports linguistics, but can also assist the study of language materials from other perspectives, such as historical, social, political or literary perspectives.

Learning goals of this course

Computational linguistics requires digital knowledge and skills. The present course therefore has the following learning goals.

Awareness of challenges and opportunities of NLP
Algorithmic thinking: breaking down tasks into processing steps
Python programming techniques for processing written text
Analyzing and visualizing linguistic datasets using Python.

This course focuses on practical programming, but there are several textbooks that introduce language and computers in some more detail. Here’s one that’s available for free: Glass, Lelia, Markus Dickinson, Chris Brew, and Detmar Meurers. 2024. Language and Computers. 2nd ed. Textbooks in Language Sciences 14. Berlin: Language Science Press. https://doi.org/10.5281/zenodo.12730906

Questions and exercises

Which areas of scholarship (within and outside of Linguistics) might benefit from computational data and tools?
Think of other applications besides machine translation.