Automatic classification and prediction of attitudes: Audio - visual analysis of video blogs

Abstract

This paper reports a study of automatic attitude recognition from a collection of over 500 segments of our video blog data. We annotated and analysed 3 different attitudinal states of the speakers. Following that, we extracted and analysed prosodic and visual features relevant to the classification task. We use machine learning methods and techniques to attain better understanding of the feature sets and their contribution to the prediction model.