Towards Online Impression Prediction of Oral Presentations Using Soft Coding
We have been developing impression prediction techniques for oral presentations. The contribution of this paper is two folds. First, we introduce soft code assignment for the bag-of-features (BoF) representation to improve the prediction accuracy. Second, we discuss towards online impression prediction aiming at real-time feedback to the speaker. Experimental results using over 1,600 TED presentation videos show that about 3% accuracy improvement can be achieved by the soft-coding and half amount of presentation is need to achieve comparable prediction accuracy to using the whole presentation.