An unsupervised approach for morphological segmentation of highly agglutinative Tamil language
Ananthi Sheshasaayee, V. R. Angela Deepa · 2015
Morphological learning through unsupervised means enables the automatic identification of affixes, morphological segmentation of words followed by the generation of paradigms incorporating the list of affixes with the combined list of stems for a particular language. For segmenting the words into stems and affixes various unsupervised approaches have been deployed. But for highly agglutinative languages like Tamil very less computational work has been done in this direction. This paper mainly portrays a morphology acquisition framework based on an unsupervised approach for the morphological segmentation of highly agglutinative Tamil language.