Unsupervised morpheme analysis with Allomorfessor

Abstract

Allomorfessor extends the unsupervised morpheme segmentation method Morfessor to account for the linguistic phenomenon of allomorphy, where one morpheme has several different surface forms. The method discovers common base forms for allomorphs from an unannotated corpus by finding small modifications, called mutations, for them. Using Maximum a Posteriori estimation, the model is able to decide the amount and types of the mutations needed for the particular language. In Morpho Challenge 2009 evaluations, the effect of the mutations was discovered to be rather small. However, Allomorfessor performed generally well, achieving the best results for English in the linguistic evaluation, and being in the top three in the application evaluations for all languages. © 2010 Springer-Verlag Berlin Heidelberg.