Morphological Cross Reference method for English to Telugu Transliteration

Machine Transliteration is a sub field of Computational linguistics for automatically converting letters in one language to another language, which deals with Grapheme or Phoneme based transliteration approaches. Several methods for Machine Transliteration have been proposed till date based on nature of languages considered, but those methods are having less precision for English to Telugu transliteration when both pronunciation and spelling of the word is considered. Morphological cross reference approach provides user friendly environment for transliteration of English to Telugu text, where both the pronunciation and the spelling of the word is taken into consideration to improve the precision of transliteration system. In addition to alphabet by alphabet transliteration, this paper also deals with whole document transliteration. Our system achieved an correct transliteration with an accuracy of '78%' of Transliteration for Vocabulary words.

[1]  Vasudeva Varma,et al.  Transliteration Based Text Input Methods for Telugu , 2009, ICCPOL.

[2]  Wei Gao,et al.  Phoneme-Based Transliteration of Foreign Names for OOV Problem , 2004, IJCNLP.

[3]  K. P. Soman,et al.  Kernel Method for English to Kannada Transliteration , 2010 .

[4]  A. P.J.,et al.  Kernel Method for English to Kannada Transliteration , 2010, 2010 International Conference on Recent Trends in Information, Telecommunication and Computing.

[5]  Shih-Hung Wu,et al.  Curate a transliteration corpus from transliteration/translation pairs , 2008, 2008 IEEE International Conference on Information Reuse and Integration.

[6]  Mohamad Shanudin Zakaria,et al.  Jawi-Malay transliteration , 2009, 2009 International Conference on Electrical Engineering and Informatics.

[7]  Guo Lei,et al.  A Supervised Method for Transliterated Person Name Identification , 2009, 2009 Second International Symposium on Electronic Commerce and Security.

[8]  Oi Yee Kwong Graphemic Approximation of Phonological Context for English-Chinese Transliteration , 2009, NEWS@IJCNLP.

[9]  Jyh-Shing Roger Jang,et al.  Extraction of transliteration pairs from parallel corpora using a statistical transliteration model , 2006, Inf. Sci..