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This paper presents an application of finite state transducers weighted with feature structure descriptions, following Amtrup (2003), to the morphology of the Semitic language Tigrinya. It is shown that feature-structure weights provide an efficient way of handling the templatic morphology that characterizes Semitic verb stems as well as the long-distance dependencies characterizing the complex Tigrinya verb morphotactics. A relatively complete computational implementation of Tigrinya verb morphology is described.

Semitic morphological analysis and generation using finite state transducers with feature structures