Abstract

We present a review of some recently developed techniques in the field of natural language processing. This area has witnessed a confluence of approaches which are inspired by theories from linguistics and those which are inspired by theories from information theory: statistical language models are becoming more linguistically sophisticated and the models of language used by linguists are incorporating stochastic techniques to help resolve ambiguities. We include a discussion about the underlying similarities between some of these systems and mention two approaches to the evaluation of statistical language processing systems. 1 Introduction Within the last decade, a great deal of attention has been paid to techniques for processing large natural language copora. The purpose of much of this activity has been to refine computational models of language so that the performance of various technical applications can be improved (e.g. speech recognisers [67], speech synthesisers [32], optica...

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