Unsupervised Learning of Morphology and the Languages of the World
Harald Hammarström · 2009
... computer extract a description of word conjugation in a natural language using only written text in the language? The problem is often referred to as Unsupervised Learning of Morphology and has a variety of applications, including Machine Translation, Document Categorization and Information Retrieval. The problem is also relevant for linguistic theory. We give a comprehensive survey of work done so far on the problem and then describe a new approach to the problem as well as a number of applications. The idea is that concatenative affixation, i.e., how stems and affixes are stringed together to form words, can, with some success, be modelled simplistically. Essentially, words consist of highfrequency strings (“affixes”) attached to low-frequency strings (“stems”), e.g., as in the English play-ing. Case studies show how this naive model can be used for stemming, language identification and bootstrapping language description. There are around 7 000 languages in the world, exhibiting a bewildering structural diversity. Linguistic Typology is the subfield of linguistics that aíms to understand this diversity. Many of the languages in the world today are