Verbal morphological analyzer/generator for Amazigh moods based on XFST
2017
This paper presents the first verbal morphological analyzer/generator for Amazigh moods using a system based on xerox's finite-state transducer platform. In this context our system is based on two main components: a lexicon including 2443 attested verbs, and a set of rules covering the morphotactic and morphological phenomena observed in standard amazigh verbs. The choice of finite-state technology makes our system bidirectional (analyzer / generator) and able to cover all variations of amazigh mood, aspect, gender, and person, and to realize an important accuracy (system recognition) which has reached about 79.07%. This system is an added value for the implementation for other applications like spellchecking, machine translation, and computer aided language learning.
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