If you have phonetically rich source data, festival will work pretty well. If you need a little more flex in your system, and can deal with a super weird training process, HTS is probably a better choice. With a small amount of work, you can use consolidated HTS models from within festival. (http://hts.sp.nitech.ac.jp/)
Further, if you pine for the fjords of DNN-land, merlin (https://github.com/CSTR-Edinburgh/merlin) is brand new and looking to make things a little easier for everybody.
But does anyone know if it's possible to do TTS with the recently released libraries?
Thanks for the links, but to my ear the samples on those links don't hit the mark. The Wavenet samples in the original article cross the threshold for me. So I'd like to try some short length dialog tests, especially as I've read elsewhere that 1 second only takes 4 minutes on a K80.
Any light anyone else can shed on this would be great.
Afaik none of the released libraries support the TTS experiment described in the paper. Deepmind used pre-computed linguistic features to guide the system in generating natural sounding speech, so your output will probably depend on the quality of those features.
For the sake of not spreading misinformation; the 4 minutes was measured using a small model with a sampling rate of 4khz, this would not generate something sounding like the samples from Deepmind.
Further, if you pine for the fjords of DNN-land, merlin (https://github.com/CSTR-Edinburgh/merlin) is brand new and looking to make things a little easier for everybody.