  The modeling of turn-taking in dialog can be viewed as the modeling of the
dynamics of voice activity of the interlocutors. We extend prior work and
define the predictive task of Voice Activity Projection, a general,
self-supervised objective, as a way to train turn-taking models without the
need of labeled data. We highlight a theoretical weakness with prior
approaches, arguing for the need of modeling the dependency of voice activity
events in the projection window. We propose four zero-shot tasks, related to
the prediction of upcoming turn-shifts and backchannels, and show that the
proposed model outperforms prior work.
