Survey on Machine Transliteration and Machine Learning Models

Globalization and growth of Internet users truly demands for almost all internet based applications to support local languages. Support of local languages can be given in all internet based applications by means of Machine Transliteration and Machine Translation. This paper provides the thorough survey on machine transliteration models and machine learning approaches used for machine transliteration over the period of more than two decades for internationally used languages as well as Indian languages. Survey shows that linguistic approach provides better results for the closely related languages and probability based statistical approaches are good when one of the languages is phonetic and other is nonphonetic.Better accuracy can be achieved only by using Hybrid and Combined models.