Unsupervised Segmentation for Different Types of Morphological Processes Using Multiple Sequence Alignment

摘要

The aim of unsupervised and knowledge free morphological segmentation is the identification of boundaries between morphs in words of a given language without relying on any knowledge source about that language. This paper describes a segmentation method that draws on previous approaches based both on semantic and orthographical similarity to identify morphologically related words. Using a version of Multiple Sequence Alignment originally applied in bioinformatics, the method extracts both concatenative and non-concatenative (e.g. introflection and circumfixation) morphological patterns and can thus handle languages of different morphological types as well as non-dominant morphological processes within languages of a particular predominant morphological type.