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Learning Swahili Morphology

Domain:

natural language processing

Record type:

paper
Creator:
GolMpi
Editor:
UniUni
Publisher:
My
Host:avatar
We describe the results of automatic morphological analysis of a large corpus of Swahili text, the Helsinki corpus, using Linguistica, an unsupervised learner of morphology. The result is a fine-grained analysis, with some results corresponding to the familiar linguistic analysis, and with others that are possible only with exact quantitative measures available with computational analysis. The prefixal inflectional morphology is largely done well, while the suffixal morphology is successfully analyzed in some cases and not in others.