  What makes a talk successful? Is it the content or the presentation? We try
to estimate the contribution of the speaker's oratory skills to the talk's
success, while ignoring the content of the talk. By oratory skills we refer to
facial expressions, motions and gestures, as well as the vocal features. We use
TED Talks as our dataset, and measure the success of each talk by its view
count. Using this dataset we train a neural network to assess the oratory
skills in a talk through three factors: body pose, facial expressions, and
acoustic features.
  Most previous work on automatic evaluation of oratory skills uses
hand-crafted expert annotations for both the quality of the talk and for the
identification of predefined actions. Unlike prior art, we measure the quality
to be equivalent to the view count of the talk as counted by TED, and allow the
network to automatically learn the actions, expressions, and sounds that are
relevant to the success of a talk. We find that oratory skills alone contribute
substantially to the chances of a talk being successful.
