  Modern text-to-speech systems are able to produce natural and high-quality
speech, but speech contains factors of variation (e.g. pitch, rhythm, loudness,
timbre)\ that text alone cannot contain. In this work we move towards a speech
synthesis system that can produce diverse speech renditions of a text by
allowing (but not requiring) explicit control over the various factors of
variation. We propose a new neural vocoder that offers control of such factors
of variation. This is achieved by employing differentiable digital signal
processing (DDSP) (previously used only for music rather than speech), which
exposes these factors of variation. The results show that the proposed approach
can produce natural speech with realistic timbre, and individual factors of
variation can be freely controlled.
