Grapheme to phoneme conversion modules are essential components in text-to-speech (TTS) systems. These modules operate before the phone sequence is fed into the synthesis routine. However, additional challenges emerge when such conversion modules are implemented with non-native varieties of languages, such as Indian English. As many of the the existing grapheme to phoneme dictionaries represent American English pronunciation, they are not suitable for use in Indian English TTS systems. Hence, in this work, an effort has been made to modify the existing English grapheme to phoneme dictionary by implementing specific rules for one particular variety of Indian English, namely Assamese English. The proposed method of dictionary modification is applied at the front end of the Indian English TTS, developed using unit selection synthesis and statistical parametric speech synthesis frameworks. In both frameworks, significant improvement is achieved in subjective evaluation when the dictionary is adapted to Assamese English pronunciation. The word error rate decreased from 46.67% to 7.69% after incorporating the variety specific modifications to the dictionary, indicating significant perceptual improvement. © 2016 IEEE.