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Reseach Article

English to Kashmiri Transliteration System - A Hybrid Approach

by Mir Aadil, M. Asger
International Journal of Computer Applications
Foundation of Computer Science (FCS), NY, USA
Volume 162 - Number 12
Year of Publication: 2017
Authors: Mir Aadil, M. Asger
10.5120/ijca2017913418

Mir Aadil, M. Asger . English to Kashmiri Transliteration System - A Hybrid Approach. International Journal of Computer Applications. 162, 12 ( Mar 2017), 5-8. DOI=10.5120/ijca2017913418

@article{ 10.5120/ijca2017913418,
author = { Mir Aadil, M. Asger },
title = { English to Kashmiri Transliteration System - A Hybrid Approach },
journal = { International Journal of Computer Applications },
issue_date = { Mar 2017 },
volume = { 162 },
number = { 12 },
month = { Mar },
year = { 2017 },
issn = { 0975-8887 },
pages = { 5-8 },
numpages = {9},
url = { https://ijcaonline.org/archives/volume162/number12/27293-2017913418/ },
doi = { 10.5120/ijca2017913418 },
publisher = {Foundation of Computer Science (FCS), NY, USA},
address = {New York, USA}
}
%0 Journal Article
%1 2024-02-07T00:08:49.455838+05:30
%A Mir Aadil
%A M. Asger
%T English to Kashmiri Transliteration System - A Hybrid Approach
%J International Journal of Computer Applications
%@ 0975-8887
%V 162
%N 12
%P 5-8
%D 2017
%I Foundation of Computer Science (FCS), NY, USA
Abstract

Named entities (NE) and Out-Of-Vocabulary (OOV) words in text are treated differently for application like Machine Translation and Information Retrieval. While normal text in the Source Language (SL) is translated on the basis of translation mapping, named entities and out-of-vocabulary are written in the script of the Target Language (TL) without any change to the articulation of the word in both the languages. The process is transliteration. This paper shows the exploitation of Phoneme-Based model for transliteration of English to Kashmiri that can be used in information extraction and machine translation for the language pair. The overall accuracy of the system achieved while tested on medical domain and Wikipedia based English text is 86% (intelligible transliteration).

References
  1. Bhalla, D. and Joshi, N. 2013 Rule Based Transliteration Scheme For English To Punjabi. International Journal on Natural Language Computing. Vol. 2 (No. 2), 67-73. .
  2. CMU. The CMU Pronunciation Dictionary. www.speech.cs.cmu.edu/cgi-bin/cmudict. School of Computer Science, Carnegie Mellon University, Pittsburgh, USA, 2006.
  3. Joshi, H., Bhatt, A. and Patel, H. 2013. Transliterated Search using Syllabification Approach. Forum for Information Retrieval Evaluation, Delhi, India.
  4. Oh, J. and Choi, K. 2002. An English-Korean Transliteration Model Using Pronunciation and Contextual Rules. In proceedings of the 19th International Conference on Computational Linguistics, Taipei, Taiwan, 758-764.
  5. https://en.wikipedia.org/wiki/Kashmiri_language#Perso-Arabic_alphabet
  6. Deep, K. and Goyal, V. (2011). Development of a Punjabi to English Transliteration System. International Journal of Computer Science and Communication. Vol. 2 (No. 2), 521-526.
  7. Josan, G. and Kaur, J. 2011. Punjabi To Hindi Statistical Machine Transliteration. International Journal of Information Technology and Knowledge Management, Vol. 4(No. 2), 459-463.
  8. Abbas R. A. and Madiha I. English to Urdu Transliteration. Proceedings of the Conference on Language & Technology, NUC and ES, Lahore, Pakistan.
Index Terms

Computer Science
Information Sciences

Keywords

Machine Transliteration Phoneme-Based Machine Transliteration English-Kashmiri Machine Transliteration.