Probabilistic and grouping methods for morphological root identification for Afaan Oromo

Abstract

Morphological models are used in many natural language processing tasks including machine translation and speech recognition. We investigated probabilistic and grouping methods to develop a morphological root identification model for Afaan Oromo. In this paper, we have experimentally shown that the proposed methods can improve the morphological root identification performance of some state-of-the-art methods.