1. Submitted to : Mr. Vimal Kumar K. Hindi Tamil Text
Translation Submitted By : Vaibhav Agarwal 10103546 Akash Singh
10103549
2. Introduction Natural Language Processing is a field of
computer science, artificial intelligence, and linguistics
concerned with the interactions between computers and human
(natural) languages. Traditionally , Interpreters having vast
knowledge of source as well as target languages have been involved
in converting text from source language to target language
manually. Machine Translation is a part of linguistics which
includes the task of automatically converting one natural language
into another, preserving the meaning of the input text, and
producing fluent text in the output language using the available
technology. 3. Aim of Research Hindi and Tamil are among the top 5
spoken languages in India with a share of 41% and 5% respectively.
Translations services like Google Translate are still working by
taking an intermediate language such as English to translate. With
this project , we have tried to directly convert Hindi text to
Tamil text without taking any intermediate language . 4.
Part-Of-Speech Tagging Process of marking up a word in a text
(corpus) as corresponding to a particular part of speech, based on
both its definition and context A simplified form of this is the
identification of words as nouns, verbs, adjectives, adverbs, etc.
Example :- 5. Statistical Machine Translation An Approach
Statistical Machine Translation (SMT) is a translation system where
translations are generated on the basis of statistical models.
These statistical models parameters are derived from the analysis
of bilingual text corpora. It is based on the view that every
sentence in a language has a possible translation in another
language. A sentence can be translated from one language to another
in many possible ways. 6. Word Sense Disambiguation (WSD) A
Challenge It is the process which governs the process of
identifying which sense of a word (i.e. meaning) is used in a
sentence, when the word has multiple meanings. For example :- 7.
Lesk Algorithm - An Approach to WSD It selects a meaning for a
particular target word by comparing the dictionary definitions of
its possible senses with those of the other content words in the
surrounding window of context It simply counts the number of words
that overlap between each sense of the target word and the sense of
other words in the sentence. 8. Architecture of Our Project Hindi
Input Part-of-Speech Tagging Apply WSD Morphological Analysis Local
Word Grouping Perform Translation & Produce Tamil Text 9.
Resource References Indian Language Technology Proliferation and
Technology Centre http://tdil-dc.in/ Centre for Indian language
Technology , IIT Bombay http://www.cfilt.iitb.ac.in/ 10. References
[1] Tripathi Sneha , Sarkhel Juran Krishna , Approaches to machine
translation, Annals of Library and Information Studies Vol 57 ,
December 2010 [2] Antony P.J. , Machine Translation Approaches and
Survey for Indian Languages , Computational Linguistics and Chinese
Language Processing Vol. 18, No. 1, March 2013 [3] Gupta Deepa ,
Chatterjee Niladri , A Morpho Syntax Based Adaptation and Retrieval
Scheme for English to Hindi EBMT , Department of Mathematics IIT
Delhi [4] Sobha Lalitha Devi, Pravin Pralayankar, Menaka S,
Bakiyavathi T, Vijay Sundar Ram R and Kavitha V , Verb Transfer in
a Tamil to Hindi Machine Translation System, 2010 International
Conference on Asian Language Processing 11. [5] Aswani Niraj,
Gaizauskas Robert . Developing Morphological Analysers for South
Asian Languages Experimenting with the Hindi and Gujarati Languages
,Department of Computer Science University of Shefeld [6]
Raghavendra Udupa U. and Tanveer A. Faruquie, An English-Hindi
Statistical Machine Translation System ,IBM India Research Lab New
Delhi [7] Amba Kulkarni, Soma Paul, Malhar Kulkarni, Anil Kumar,
Nitesh Surtani ,Semantic processing of Compounds in Indian
Languages [8] Pankaj Kumar , Atul Vishwakarma , Ashwini Kr. Sharma
, Approaches for Disambiguation in Hindi Language
