Before revision:   However, we observe that  completely dispensing with any duration modelling introduces occasional instabilities in the generated spectrograms. We train an autoregressive WaveNet to be used as a neural vocoder to synthesise the mel-spectrograms produced by the sequence-to-sequence architecture, using a combination of speech and singing data .
After revision:  However, we observe that completely dispensing with any explicit duration modelling it becomes harder to obtain the fine control of timing needed to exactly match the tempo of a song .