In this paper, we aim to predict audience response
from simple spoken sequences, speech pauses and co-speech
gestures in annotated video- and audio-recorded speeches by
Barack Obama at the Annual White House Correspondents’
Association Dinner in 2011 and 2016. At these dinners, the
American president mocks himself, his collaborators, political
adversary and the press corps making the audience react with
cheers, laughter and/or applause. The results of the prediction experiment
demonstrate that information about spoken sequences,
pauses and co-speech gestures by Obama can be used to predict
the immediate audience response. This confirms and shows an
application of numerous studies that address the importance of
speech pauses and gestures in delivering the discourse message
in a successful way. The fact that machine learning algorithms
can use information about pauses and gestures to build models
of audience reaction is also relevant for the construction of
intelligent and cognitively based multimodal ICT.