Paper: Unsupervised Discovery Of Phonological Categories Through Supervised Learning Of Morphological Rules

ACL ID C96-1018
Title Unsupervised Discovery Of Phonological Categories Through Supervised Learning Of Morphological Rules
Venue International Conference on Computational Linguistics
Session Main Conference
Year 1996
Authors

We describe a case study in tit(', ap- plication of symbolic machinc learning techniques for the discow;ry of linguis- tic rules and categories. A supervised rule induction algorithm is used to learn to predict the. correct dimilmtive suffix given the phonological representation of Dutch nouns. The system produces rules which are comparable, to rules proposed by linguists, l,Slrthermore, in the process of learning this morphological task, the phonemes used are grouped into phono- logically relevant categories. We discuss the relevance of our method for linguis- tics attd language technology.