LANGUAGE IN INDIA

Strength for Today and Bright Hope for Tomorrow

Volume 16:11 November 2016
ISSN 1930-2940

Managing Editor: M. S. Thirumalai, Ph.D.
Editors: B. Mallikarjun, Ph.D.
         Sam Mohanlal, Ph.D.
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         Jennifer Marie Bayer, Ph.D.
         G. Baskaran, Ph.D.
         L. Ramamoorthy, Ph.D.
         C. Subburaman, Ph.D. (Economics)
         N. Nadaraja Pillai, Ph.D.
         Renuga Devi, Ph.D.
         Soibam Rebika Devi, M.Sc., Ph.D.
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English-Hindi TAM Divergence in Relation to Anusaaraka

Neha Maurya, M.A., Ph.D. Scholar
Shubhra Apurve, M.A., Ph.D. Scholar
Manish Singh, M.A., Ph.D. Scholar
Madhavi, M.A., Ph.D. Scholar
Saurabh Srivastav, M.A., Ph.D.
Ruchi Singh, M.A., Ph.D.


Abstract

Tense aspect and modality (TAM) play a crucial role in defining syntactic, semantics and discourse structure in a sentence. The paper looks at TAM-related issues and attempts to formulate rules of their disambiguation in the context of English-Hindi machine translation (MT) system Anusaaraka. It is impossible to find out exact one-to-one mapping of each English TAM into Hindi TAM. The present work is in the initial stage. We have worked on total 318 English TAMs, which are introduced with their Hindi TAM. In this paper we have collected the example sentences for each English TAM and translate them into Hindi. Then, we have found tam divergence issues and classify the main issues linguistically. We first check these TAM and found the examples and counter examples from COCA (The Corpus of Contemporary American English). Then, we run these sentences in Anusaaraka MT. We have got eight issues like, Perfect continuous markers, Passive to Active, hypothetical mood in English cannot captured in Hindi, would and could do not have any past equivalent in Hindi, modality based divergence, one-to-one and many-to-one mapping in English-Hindi, and rest of the issues which are not covered any specific area, could projected in others group. Thus, the main claim of this paper is to focus on these eight issues and gives the way for solution.

Keywords: Tense, Aspect, Modality, English-Hindi MT, Anusaaraka, TAM divergence

Introduction

1. All natural languages are rich in marking Tense, Aspect and modality. These Tense aspect and modality play a crucial role in defining not only syntactic position in a sentence but on semantics and discourse level too. These function together, so these are knowns as TAM. It is a well-known for linguist and computational linguist. They are needed for specifying the information about the world which is temporal in nature, or tell us something about the status of an action, or about the ability to perform an action. In some languages, they also govern the realization of a particular case marker. Different languages have different systems for marking such temporal including aspectual and modal information. In other words, TAM markers used by different languages don’t have a one- to-one correspondence, So this has become a crucial problem in Machine translation. There are number of errors come through TAM markers.


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Neha Maurya, M.A., Ph.D. Scholar(Thesis Submitted)
neha.mourya08@gmail.com

Shubhra Apurve, M.A., Ph.D. Scholar
shubhraapurve@gmail.com

Manish Singh, M.A., Ph.D. Scholar
maneeshhsingh100@gmail.com

Madhavi, M.A., Ph.D. Scholar(Thesis Submitted)
madhavimanya.kush@gmail.com

Saurabh Srivastav, M.A., Ph.D.. Scholar
saurabh0780@gmail.com

Ruchi Singh, M.A., Ph.D. Scholar
ruchisingh.linguistics@gmail.com

Department of Linguistics
Banaras Hindu University
Varanasi 221005
Uttar Pradesh
India

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