Towards Finite-State Morphology of Kurdish
This work addresses the lack of computational resources for Kurdish, a less-resourced language, by providing foundational tools for NLP tasks, though it is incremental as it applies existing finite-state methods to a new language.
The authors tackled the problem of morphological analysis for the under-resourced Kurdish language (Sorani dialect) by extracting morphological rules and transforming them into finite-state transducers, resulting in a computational description that aids in language generation and information retrieval tasks.
Morphological analysis is the study of the formation and structure of words. It plays a crucial role in various tasks in Natural Language Processing (NLP) and Computational Linguistics (CL) such as machine translation and text and speech generation. Kurdish is a less-resourced multi-dialect Indo-European language with highly inflectional morphology. In this paper, as the first attempt of its kind, the morphology of the Kurdish language (Sorani dialect) is described from a computational point of view. We extract morphological rules which are transformed into finite-state transducers for generating and analyzing words. The result of this research assists in conducting studies on language generation for Kurdish and enhances the Information Retrieval (IR) capacity for the language while leveraging the Kurdish NLP and CL into a more advanced computational level.