Third European Conference on Speech Communication and Technology

Berlin, Germany
September 22-25, 1993


Integration of Neural Networks and Robust Parsers in Natural Language Understanding

Ying Cheng (1,2), Yves Normandin (1), Paul Fortier (2)

(1) CRIM, Montreal, Quebec, Canada
(2) Dept. of Electrical Engineering, Laval University, Quebec, Canada

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.

Full Paper

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.