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The field of natural language processing (NLP) originated approximately five decades ago withmachine translation systems. In 1946, Warren Weaver and Andrew Donald Booth discussed thetechnical feasibility of machine translation “by means of the techniques developed during WorldWar II for the breaking of enemy codes” (Booth and Locke, 1955, p. 2). During the more than fiftyyears of its existence, the field has evolved from the dictionary-based machine translation systemsof the fifties to the more adaptable, robust, and user-friendly NLP environments of the nineties.This evolution has been marked by periods of considerable growth and funding “prosperity,”followed by years of intense criticism and lack of funding. This article attempts to provide anoverview of this field by focusing on its history, current trends, some important theories andapplications, and the state-of-the-art as it relates to human-computer interaction (HCI).

Currently, the field of NLP includes a wide variety of linguistic theories, cognitive models, andengineering approaches. Although unrestricted NLP is still a very complex problem (and accordingto some, an AI-complete problem2), numerous successful systems exist for restricted domains of Similarly to the concept of NP-complete problems, the term AI-complete has been used to describeproblems, that can only be solved if a solution to the “general” AI problem has been discovered(Carbonell, 1996). Some argue that such problems are unsolvable (Dreyfus, 1993); others suggest that discourse. In the context of HCI, NLP applications range from various speech recognition systems,to natural language interfaces to database, expert, and operating systems, to a multitude ofmachine translation systems. Currently, interactive applications may be classified along thefollowing categories (Manaris and Slator, 1996; Obermeier, 1988): Download free Natural Language Processing: A Human–Computer Interaction Perspective.pdf here