A Survey on Morph Analyzers for Indian Languages

Abstract

Computational Morphology of natural language is a challenging task incorporated from Computational
Linguistics (CL), an applied area of NLP diverged from Artificial Intelligent (AI). Heading towards the assembling a
robust Machine Translation (MT) system, Morphological analyzer (MA) is the vital stages where the words are picked to
analyzed up to the minimal meaningful unit of that language. The ample of morphological analyzer applications have
been developed which covers all the possible approaches of machine learning which clearly stats the output of the
application, procedure of development and possible up-gradation throughout the time. This paper is a survey
incorporated with all the survey of research work done on MA and having an aim to discover a most feasible approach
could be elected for the development of Maithili Morphological Analyzer. Keeping such vision, all the research papers of
MA-IL is reviewed and diagnosed at various levels, the most used mechanism would be applied with possible
modification to meet our aim and also analyze it with all the related morpheme features. This survey is absolutely
motivated based on all the MA-IL applications having various approaches like Algorithm, accuracy, and attached
features. And up to what extent the elected approach would help to develop Maithili MA with robust accuracy.