The field overlapped with artificial intelligence since the efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English.
[1] Since rule-based approaches were able to make arithmetic (systematic) calculations much faster and more accurately than humans, it was expected that lexicon, morphology, syntax and semantics can be learned using explicit rules, as well.
It consisted of IBM computer manuals, transcribed telephone conversations, and other texts, together containing over 4.5 million words of American English, annotated using both part-of-speech tagging and syntactic bracketing.
Using the Price equation and Pólya urn dynamics, researchers have created a system which not only predicts future linguistic evolution but also gives insight into the evolutionary history of modern-day languages.
[9] Research in this area combines structural approaches with computational models to analyze large linguistic corpora like the Penn Treebank, helping to uncover patterns in language acquisition.