  Filled pauses (or fillers), such as "uh" and "um", are frequent in
spontaneous speech and can serve as a turn-holding cue for the listener,
indicating that the current speaker is not done yet. In this paper, we use the
recently proposed Voice Activity Projection (VAP) model, which is a deep
learning model trained to predict the dynamics of conversation, to analyse the
effects of filled pauses on the expected turn-hold probability. The results
show that, while filled pauses do indeed have a turn-holding effect, it is
perhaps not as strong as could be expected, probably due to the redundancy of
other cues. We also find that the prosodic properties and position of the
filler has a significant effect on the turn-hold probability. However, contrary
to what has been suggested in previous work, there is no difference between
"uh" and "um" in this regard.
