Development of Morphological Stemmer, Analyzer and Generator for Kannada Nouns

Abstract

Kannada is an inflectional and morphologically rich language. Developing a well-fledged morphological stemmer, analyzer, and generator (MSAG) model for Kannada is a challenging task. In any natural language processing applications, there is a great demand for MSAG model. In this paper, a hybrid MSAG model is proposed as a part of machine translation system from Kannada to any other language. This model is developed using suffix-stripping, rule-based, and paradigm-based approaches. The performance of this model is tested against a set of nouns randomly taken from a well-known dictionary called ''Kannada Rathna Kosha'' [1].