  Although Sequence-to-Sequence (S2S) architectures have become
state-of-the-art in speech synthesis, capable of generating outputs that
approach the perceptual quality of natural samples, they are limited by a lack
of flexibility when it comes to controlling the output. In this work we present
a framework capable of controlling the prosodic output via a set of concise,
interpretable, disentangled parameters. We apply this framework to the
realization of emphatic lexical focus, proposing a variety of architectures
designed to exploit different levels of supervision based on the availability
of labeled resources. We evaluate these approaches via listening tests that
demonstrate we are able to successfully realize controllable focus while
maintaining the same, or higher, naturalness over an established baseline, and
we explore how the different approaches compare when synthesizing in a target
voice with or without labeled data.
