Comparative Analysis of Morphological Approaches for Low-Resource Indo-Aryan Languages: Case Studies in Angika, Maithili, and Hindi

Morphological analysis is important and challenging sub-task in Natural Language Processing (NLP), particularly for morphologically rich Indo-Aryan languages. Yet, some regional languages as Angika and Maithili are still under-resourced due to the absence of annotated corpora and compu- tational tools. This work is a comparative study of morphological analysis in the context of Angika, Maithili and Hindi, covering low-and little-resource scenarios. The work compares rule-based, finite-state transducer and hybrid methods and concentrates on the treatment of inflectional and derivational morphology. Linguistically motivated rules and small lexical re- sources are used for low resource languages, while Hindi is used as a reference language. Rule-based and hybrid models perform more robustly and have better interpretable results in low-resource settings than the purely data-driven models. The study demonstrates the need for LingA (linguistic analyzers) to seamlessly combine linguistic knowl- edge with computational techniques, in order to develop efficient morpho-analysis tools for Indo-Aryan lan- guages that are still under-represented typologically.