In this paper, we have presented a method for adapting a language generator to the strengths and weaknesses of a particular synthetic voice by training a discriminative reranker to select paraphrases that are predicted to sound natural when synthesized.
to previous work on this topic, our method can be employed with any speech synthesizer in principle, so long as features derived from the synthesizer's unit selection search can be made available.