Automatic Processing of Amazighe Verbal Morphology: a New Approach for Analysis and Formalization
Fatima Zahra Nejme, Siham Boualknadel, Driss Aboutajdine · International Review on Computers and Software (IRECOS) · 2015
Due to the rich morphology and the highly complex word formation process of roots and patterns, Amazighe morphology processing poses special challenges to Natural Language Processing (NLP) systems. In this paper we present the architecture and implementation details of lexicon and the morphological descriptions for building a Verb Morphological Analyzer. Our main contribution in this paper consists of two main components: firstly, a linguistically motivated tool based on the concept of patterns and allows, from a verbal entries, to predict the inflectional forms. Then, a set of rules covering a set of orthographical constraint and grammaticalization rules observed in the treatment process. Our analyzer exploits the efficiency and flexibility offered by finite state machines in modeling while using the NooJ Finite State tools