Computational Linguistics

Computational linguistics is an interdisciplinary field concerned with the statistical or rule-based modeling of natural language from a computational perspective.

Traditionally, computational linguistics was performed by computer scientists who had specialized in the application of computers to the processing of a natural language. But little if any success was made. Computational linguists often work as members of interdisciplinary teams, which can include regular linguists, experts in the target language, and computer scientists. In general, computational linguistics draws upon the involvement of linguists, computer scientists, experts in artificial intelligence, mathematicians, logicians, philosophers, cognitive scientists, cognitive psychologists, psycholinguists, anthropologists and neuroscientists, among others.

Computational linguistics has theoretical and applied components. Theoretical computational linguistics focuses on issues in theoretical linguistics and cognitive science, and applied computational linguistics focuses on the practical outcome of modeling human language use.

The Association for Computational Linguistics defines computational linguistics as:

Computational linguistics is often grouped within the field of artificial intelligence, but actually was present before the development of artificial intelligence. Computational linguistics originated with efforts in the United States in the 1950s to use computers to automatically translate texts from foreign languages, particularly Russian scientific journals, into English. Since computers can make arithmetic calculations much faster and more accurately than humans, it was thought to be only a short matter of time before they could also begin to process language. Computational and quantitative methods are also used historically in attempted reconstruction of earlier forms of modern languages and subgrouping modern languages into language families. Earlier methods such as lexicostatistics and have been proven to be premature and inaccurate. However, recent interdisciplinary studies which borrow concepts from biological studies, especially gene mapping, have proved to produce more sophisticated analytical tools and more trustful results.

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