Abstract

This paper describes in detail an algorithm for the unsupervised learning of natural language morphology, with emphasis on challenges that are encountered in languages typologically similar to European languages. It utilizes the Minimum Description Length analysis described in Goldsmith 2001 and has been implemented in software that is available for downloading and testing. 1. Scope of this paper This paper describes in detail an algorithm used for the unsupervised learning of natural language morphology which works well for European languages and other languages in which the average number of morphemes per word is not too high. 1 It has been implemented and tested in Linguistica, and is based on the theoretical principles described in Goldsmith 2001. The present paper describes that framework briefly, but the reader is referred there for a more careful development. The executable for this program, and the source code as well, is available at

Citations