Samples of Paper RawNet: Fast End-to-End Neural Vocoder, which is submitted to Interspeech 2019.
RawNet, is a truly end-to-end neural vocoder, which use a coder network to learn the higher representation of signal, and an autoregressive voder network to generate speech sample by sample. The coder and voder together act like an auto-encoder network, and could be jointly trained directly on raw waveform without any human-designed features.
More detail is explained in the paper.
Code will be released soon...
In the RawNet samples directory, you can find the demo samples generated by RawNet.
Yunchao He