Smriti Singh

IIT Bombay, Humanities and Social Sciences, Graduate Student

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An experienced linguist working in the area of NLP and Data sciences

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Verbal Inflection in Hindi: A Distributed Morphology Approach

In this paper, we provide a complete description of Hindi verbal inflection within the framework ... more In this paper, we provide a complete description of Hindi verbal inflection within the framework of Distributed morphology. We discuss the categories that are visible on the verb itself and on associated auxiliaries. We show how both analysis and generation are possible using this model. We also discuss the implementation of such linguistically motivated analysis in a morphological analyzer for Hindi, one of the several NLP tools that we have developed for Hindi, and discuss the outcomes of such an implementation. In this paper, we present an analysis of Hindi verbal inflection in the framework of Distributed Morphology (DM) (Halle and Marantz 1993 1994, Harley and Noyer 2003). The analysis presented in this paper demonstrates how DM may be used to provide a systematic and economical account of verbal inflection in Hindi. This DM analysis also lends itself straightforwardly to implementation in a Hindi Morphological Analyzer. We begin by detailing the different inflectional categori...

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Hindi Noun Inflection and Distributed Morphology

Université Paris Diderot, Paris …

Hindi Noun Inflection and Distributed Morphology Smriti Singh and Vaijayanthi M. Sarma Indian Ins... more Hindi Noun Inflection and Distributed Morphology Smriti Singh and Vaijayanthi M. Sarma Indian Institute of Technology Bombay, India Proceedings of the ... We also thank P. Bhattacharyya and O. Damani (IIT Bombay) for their input and support and Nikhilesh Sharma who helped ...

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Noun Group and Verb Group Identification for Hindi

We present algorithms for identifying Hindi Noun Groups and Verb Groups in a given text by using ... more We present algorithms for identifying Hindi Noun Groups and Verb Groups in a given text by using morphotactical constraints and sequencing that apply to the constituents of these groups. We provide a detailed repertoire of the grammatical categories and their markers and an account of their arrangement. The main motivation behind this work on word group identification is to improve the Hindi POS Tagger's performance by including strictly contextual rules. Our experiments show that the introduction of group identification rules results in improved accuracy of the tagger and in the resolution of several POS ambiguities. The analysis and implementation methods discussed here can be applied straightforwardly to other Indian languages. The linguistic features exploited here are drawn from a range of well-understood grammatical features and are not peculiar to Hindi alone.

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Verbal Inflection in Hindi: A Distributed Morphology Approach

PACLIC 2011

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Hindi Noun Inflection and Distributed Morphology

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Hindi Generation From Interlingua

… Summit (MTS 07), …, Jan 1, 2007

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Morphological Richness Offsets Resource Demand-Experiences In Constructing a POS Tagger for Hindi

Proceedings of the …, Jan 1, 2006

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Harnessing Morphological Analysis In POS Tagging Task

Proceedings of the …, Jan 1, 2005

Harnessing Morphological Analysis in POS Tagging Task Manish Shrivastava, Nitin Agrawal, Smriti S... more Harnessing Morphological Analysis in POS Tagging Task Manish Shrivastava, Nitin Agrawal, Smriti Singh and Pushpak Bhattacharya Department of Computer Science and Engineering, Indian Institute of Technology, Bombay, Mumbai-76, India E-mail: manshri. ...

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MTeval: An Evaluation Methodology for Machine Translation Systems

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Smriti Singh

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