LANGUAGE IN INDIA

Strength for Today and Bright Hope for Tomorrow

Volume 11 : 5 May 2011
ISSN 1930-2940

Managing Editor: M. S. Thirumalai, Ph.D.
Editors: B. Mallikarjun, Ph.D.
         Sam Mohanlal, Ph.D.
         B. A. Sharada, Ph.D.
         A. R. Fatihi, Ph.D.
         Lakhan Gusain, Ph.D.
         Jennifer Marie Bayer, Ph.D.
         S. M. Ravichandran, Ph.D.
         G. Baskaran, Ph.D.
         L. Ramamoorthy, Ph.D.

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Statistical Machine Translation using Joshua -
An approach to build “enTel” system

Anitha Nalluri and Vijayanand Kommaluri

This paper addresses an approach to build “enTel” System – An English to Telugu Machine Translation (MT) System using Statistical Machine Translation (SMT) techniques and Johns Hopkins University Open Source Architecture (JOSHUA).

It provides a heuristic approach - To train a probabilistic alignment model and use its predictions to align words and ensure the well form of the target language sentences - The tuning of weights of model to balance the contribution of each of the component parts to find the optimal weights among different models – Evaluation of the quality of machine translation with the Bilingual Evaluation Understudy (BLEU) that compares a system's output against reference human translations.

This is only the beginning part of the article. PLEASE CLICK HERE TO READ THE ARTICLE IN PRINTER-FRIENDLY VERSION.

Anitha Nalluri
Advisory System Analyst
IBM India
Bangalore, India
analluri@in.ibm.com

Vijayanand Kommaluri
Assistant Professor
Department of Computer Science
Pondicherry University
Puducherry, India
kvpudu@gmail.com
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