This article surveys work on Unsupervised Learning of Morphology. We define Unsupervised Learning of Morphology as the problem of inducing a description (of some kind, even if only morpheme segmentation) of how orthographic words are built up given only raw text data of a language. We briefly go through the history and motivation of this problem. Next, over 200 items of work are listed with a brief characterization, and the most important ideas in the field are critically discussed. We summarize the achievements so far and give pointers for future developments.
Most work on unsupervised learning of morphology has focused on concatenative morphology REF .
Unsupervised Learning of Morphology
Computational Linguistics
Computational Linguistics
Computer Science