Transliterated Search using Syllabification Approach

Machine transliteration refers to the process of automatic conversion of a word from one language to another without losing its phonological characteristics. In this work, we present our experiments performed in subtask-1 and subtask-2 as a part of the FIRE-2013 transliterated search task. In both the subtasks, the transliteration from Roman script to Devanagari script was performed using syllabification approach that converted English into Hindi language. In the query labeling subtask, identification of English and Hindi words was performed using a hybrid approach that involved morphological analysis of English words and a corpus based approach to identify frequently occurring Hindi words. In the multi-script adhoc retrieval of Hindi song lyrics subtask, the queries were formulated that contained both Roman and Devanagari script and Roman script for separate run submissions. The evaluation of our experiments achieved a higher recall value of query labeling in subtask-1 however the results of subtask-2 are indicating average performance.