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Verbal morphological analyzer/generator for Amazigh moods based on XFST

Authors: Rachid Ammari; L Zenkouar; M. Outahajala;

Verbal morphological analyzer/generator for Amazigh moods based on XFST

Abstract

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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selected citations
These citations are derived from selected sources.
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Citations provided by BIP!
popularity
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
BIP!Popularity provided by BIP!
influence
This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
BIP!Influence provided by BIP!
impulse
This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.
BIP!Impulse provided by BIP!
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