We report in this paper a novel hybrid approach for Urdu to Hindi transliteration that combines finite-state machine (FSM) based techniques with statistical word language model based approach. The output from the FSM is filtered with the word language model to produce the correct Hindi output. The main problem handled is the case of omission of diacritical marks from the input Urdu text. Our system produces the correct Hindi output even when the crucial information in the form of diacritic marks is absent. The approach improves the accuracy of the transducer-only approach from 50.7% to 79.1%. The results reported show that performance can be improved using a word language model to disambiguate the output produced by the transducer-only approach, especially when diacritic marks are not present in the Urdu input.
As reported in REF ) these hand designed rules achieve accuracies of only about 50% in the absence of diacritical marks.
A Hybrid Model for Urdu Hindi Transliteration
Proceedings of the 2009 Named Entities Workshop: Shared Task on Transliteration (NEWS 2009)
Computer Science