Paper: Neural Network Approach To Word Category Prediction For English Texts

ACL ID C90-3038
Title Neural Network Approach To Word Category Prediction For English Texts
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1990
Authors

Word category prediction is used to implement an accurate word recognition system. Traditional statistical approaches require considerable training data to estimate the probabilities of word sequences, and many parameters to memorize probabilities. To solve this problem, NETgram, which is the neural network for word category prediction, is proposed. Training results show that the perfornmnce of tim NETgram is comparable to that of the statistical model ;although the NETgram requires fewer parameters than the ~;tatisticat model. Also the NETgram performs effectively £or unknown data, i.e., the NETgram interpolates sparse training data. Results of analyzing the hidden layer show that the word categories are classified into linguistically ti~ignificant groups. The results of applying the NET...