The application of neural networks to natural language translation.

Abstract

The characteristics of automated learning and generalization, and of graceful degradation in the face of unforeseen input, give neural networks interesting potential for machine translation (MT). However, the field of connectionist MT has been little explored by researchers. This thesis provides an introduction to neural network concepts and summarizes and reviews the research in the field of connectionist MT. It describes the building, training and testing of TransNet, an embryonic neural network that translates weather reports from English into French. TransNet uses an innovative bigram (word pair) data representation which makes it possible to take some account of word order in the processing.