Speech understanding systems (SUS's) came of age in late 1971 as a result of a five year development programme instigated by the Information Processing Technology Office of the Advanced Research Projects Agency (ARPA) of the Department of Defense in the United States. The aim of the programme was to research and develop practical man-machine communication systems. It has been argued since, that the main contribution of this project was not in the development of speech science, but in the development of artificial intelligence. That debate is beyond the scope of this paper, though no one would question the fact that the field to benefit most within artificial intelligence as a result of this programme is natural language understanding. More recent projects of a similar nature, such as projects in the United Kingdom's ALVEY programme and Europe's ESPRIT programme have added further developments to this important field. This paper presents a review of some of the natural language processing techniques used within speech understanding systems. In particular, techniques for handling syntactic, semantic and pragmatic information are discussed. They are integrated into SUS's as knowledge sources. The most common application of these systems is to provide an interface to a database. The system has to perform a dialogue with a user who is generally unknown to the system. Typical examples are train and aeroplane timetable enquiry systems, travel management systems and document retrieval systems.