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Hindi grapheme-to-phoneme (G2P) conversion is mostly trivial, with oneexception: whether a schwa represented in the orthography is pronounced orunpronounced (deleted). Previous work has attempted to predict schwa deletionin a rule-based fashion using prosodic or phonetic analysis. We present thefirst statistical schwa deletion classifier for Hindi, which relies solely onthe orthography as the input and outperforms previous approaches. We trainedour model on a newly-compiled pronunciation lexicon extracted from variousonline dictionaries. Our best Hindi model achieves state of the artperformance, and also achieves good performance on a closely related language,Punjabi, without modification.

Supervised Grapheme-to-Phoneme Conversion of Orthographic Schwas in Hindi and Punjabi