Abstract

This paper primarily presents an analysis of nominal inflection in Hindi within the framework of Distributed Morphology (Halle & Marantz 1993, 1994 and Harley and Noyer 1999). Müller (2002, 2003, 2004) for German, Icelandic and Russian nouns respectively and Weisser (2006) for Croatian nouns have also used Distributed Morphology (henceforth DM) to analyze nominal inflectional morphology. This paper will discuss in detail the inflectional categories and inflectional classes, the morphological processes operating at syntax, the distribution of vocabulary items and the readjustment rules required to describe Hindi nominal inflection. Earlier studies on Hindi inflectional morphology (Guru 1920, Vajpeyi 1958, Upreti 1964, etc.) were greatly influenced by the Paninian tradition (classical Sanskrit model) and work with Paninian constructs such as root and stem. They only provide descriptive studies of Hindi nouns and verbs and their inflections without discussing the role or status of affixes that take part in inflection. The discussion on the mechanisms (morphological operations and rules) used to analyze or generate word forms are missing in these studies. In addition, these studies do not account for syntax-morphology or morphology-phonology mismatches that show up in word formation. One aim of this paper is to present an economical way of forming noun classes in Hindi as compared to other traditional methods, especially gender and stem ending based or paradigm based methods that give rise to a large number of inflectional paradigms. Using inflectional class information to analyse the various forms of Hindi nouns, we can reduce the number of affixes and word-generation and readjustment rules that are required to describe nominal inflection. The analysis also helps us in developing a morphological analyzer for Hindi. The small set of rules and fewer inflectional classes are of great help to lexicographers and system developers. To the best of our knowledge, the analysis of Hindi inflectional morphology based on DM and its implementation in a Hindi morphological analyzer has not been done before. The methods discussed here can be applied to other Indian languages for analysis as well as word generation.

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