Tacotron-2

ology. Without the invention of AGI, the TTS models do not understand the underlying text; therefore, it'll be unable to do more "complex things with intonation/prosody". Furthermore, the models suffer from overfitting. The model performance degrades significantly when performing TTS on text not typically seen in the training data.

-- > he didn’t actually endorse our work like this, it’s a clip from the video the team created featuring their work. Video and more after the jump! It's absolutely unresponsible/illegal to clone a person's voice without consent. To use Joe Rogan's likeness for your publicity stunt without his consent is unethical in its self. It's Joe Rogan's legal right to control his own likeness. Furthermore, this presents a number of safety risks to Joe Rogan including the possibility of identity fraud. -------------------------------------------------- Finally, at this time, TTS human parity technology is at human-parity when tested on phrases and sentences similar to those in the training set. Google's Tacotron-2 models showed a significant decrease in performance reading 37 news headlines. They mentioned in their evaluation: > This result points to a challenge for end-to-end approaches – they require training on data that cover intended usage.

s high as WaveNet. I'd really like to tie in with WaveGlow, but it's work in progress for me so far. NOTE: None of these have voice adaptivity per se, but given a model which trains well already + a multispeaker dataset with IDs such as VCTK, a lot of things become possible as getting a baseline model and data pipeline for TTS is quite difficult. [0] https://github.com/keithito/tacotron [1] https://r9y9.github.io/blog/2018/05/20/tacotron2/ [2] https://github.com/Rayhane-mamah/Tacotron-2 [3] https://github.com/NVIDIA/waveglow [4] https://github.com/NVIDIA/tacotron2