Morphological Analyzer for Kokborok

Morphological analysis is concerned with retrieving the syntactic and morphological properties or the meaning of a morphologically complex word. Morphological analysis retrieves the grammatical features and properties of an inflected word. However, this paper introduces the design and implementation of a Morphological Analyzer for Kokborok, a resource constrained and less computerized Indian language. A database driven affix stripping algorithm has been used to design the Morphological Analyzer. It analyzes the Kokborok word forms and produces several grammatical information associated with the words. The Morphological Analyzer for Kokborok has been tested on 56732 Kokborok words; thereby an accuracy of 80 % has been obtained on a manual check

Part of Speech (POS) Tagger for Kokborok

The Part of Speech (POS) tagging refers to the process of assigning appropriate lexical category to individual word in a sentence of a natural language. This paper describes the development of a POS tagger using rule based and supervised methods in Kokborok, a resource constrained and less computerized Indian language. In case of rule based POS tagging, we took the help of a morphological analyzer while for supervised methods, we employed two machine learning classifiers, Conditional Random Field (CRF) and Support Vector Machines (SVM). A total of 42,537 words were POS tagged. Manual checking achieves the accuracies of 70 % and 84 % in case of rule based and supervised POS tagging, respectively