Before revision:  In this work we show that , in the case of a well-curated French dataset, graphemes can be used as input without increasing the amount of pronunciation errors. Furthermore, we perform an analysis of the representation learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.
After revision:  In this work we show that , in the case of grapheme inputs, little is known concerning the relation between the underlying representations learned by the Tacotron model and show that the contextual grapheme embeddings encode phoneme information , and that they can be used for grapheme-to-phoneme conversion and phoneme control of synthetic speech.