This paper provides an introduction to the syntactic and semantic sub-system of AURAID: a speech recognition aid for use by deaf students in lectures. This sub-system produces a useful word recognition level from a continuous sequence of phonemes as could be provided by a continuous speech phoneme recognition system. The dynamic programming stage matches the phoneme input with a dictionary to produce a word lattice. The parsing stage makes use of an "anti-grammar" and semantic categories in order to determine the best sequence of words through the lattice. AURAID has a vocabulary of 2200 words and works in real-time using a simulated continuous speech phoneme recognition system (modelled on the performance of the DRA (UK) Speech Research Unit's Armada system). The phoneme error rate provided by this simulation is approximately 26%. Word recognition rates of approximately 85% have been achieved on sections of the simulated data using unrestricted speech. The simulated data is taken from real University lectures on the subject of software engineering.

Keywords: continuous speech recognition, spontaneous speech, grammar, semantic categories