Emotion Recognition from Speech

Abstract

In this position paper we present an approach for the recognition of emotions from speech. Our goal is to understand the affective state of learners upon a learning process. We propose an approach that uses visual representations of the spectrum of audio segments, which are classified using the Bag-of-Visual Words model. Our approach is applied on a real-life dataset that contains interviews from middle-school students, collected upon a classroom experiment.