Introduction

Natural Language Processing (NLP) also called language technology, linguistic engineering and computational linguistics aims to study and develop methods by which "natural" human languages can be processed effectively by computer.
NLP has the potential to make a very significant contribution to the usefulness of information technology in the long term future. Some key growth areas are:

• automatic localisation of software and its documentation (via language translation)
• information retrieval
• machine assisted translation
• grammatical and stylistic analysis
• natural language interfaces for databases

There has recently been an explosion in this field as the computer hardware available to home users achieves a level where real-time processing is possible.
A growing number of groups are discovering the potential of large scale linguistic resources such as machine readable dictionaries, tagged linguistic manuscripts and bi-lingual texts. The existence of these resources has allowed the development of NLP system components such as part-of-speech taggers and machine tractable lexicons.
Standards are being established for the representation of linguistic components in a machine-readable form. Internationally supported projects such as the Text Encoding Initiative have recently appeared with the specific objective of creating and disseminating such standards.
There is a move towards freer exchange of information, data and software between groups. This is exemplified by the growing number of electronic newsgroups dedicated to NLP, and by the formation of international clearing houses such as the Consortium for Lexical Research. Access to these resources has been greatly facilitated by the extension of the internet to Europe.
The fields of text processing and natural language processing are gradually converging. For example style checkers are often incorporated into word processors. Developments of this kind are greatly expanding the potential market for NLP products.
There is a huge field being studied that involves speech recognition and speech synthesis. These areas are beyond the scope of this research, however it is clear that speech recognition will be able to provide higher levels of language comprehension accuracy due to the added components of stress, accenting and pauses.