A Memory Based approach to Malayalam noun generation

Words are the important building blocks of every language. Morphological generator is used to get the inflected form of a word, given its root word and a set of properties such as lexical category and morphological properties. Morphological Generation and analysis are necessary for developing computational grammars as well as machine translation systems. This paper presents a morphological generator for Malayalam nouns using Memory Based Language Processing (MBLP) approach. MBLP is an approach to language processing based on exemplar storage during learning, and analogical reasoning during processing. For training the system, a training corpus is created. It contains the basic examples of root words and their features. The feature set for this Malayalam noun generation system includes number, case, and the last syllable of the root word. Tilburg Memory based Learner (TiMBL) is used for training the system. The system doesn´t require a dictionary or rules for its working. It gives a satisfactory result, having an accuracy of 93.68%.