In this paper, we describe a natural language understanding system which focuses on spoken language and integrates a neural network classifier and robust parsers. With the help of classification, the application domain is divided into several subsets. Parsers are constructed for each subset and as a result, the complexity of grammar construction is much smaller than if a grammar for the whole application domain had to be constructed. Furthermore, by using a neural network, our goal was to take the advantage of its learning ability and robustness to noise. Although the system was implemented in a short time, it performed reasonably well in its first participation in a DARPA ATIS (Air Travel Information System) evaluation in Nov. 92. It was quite robust to speech recognition errors in particular.
Keywords: neural network, parser, natural language understanding.
Bibliographic reference. Cheng, Ying / Normandin, Yves / Fortier, Paul (1993): "Integration of neural networks and robust parsers in natural language understanding", In EUROSPEECH'93, 1311-1314.