Annotation practices in affective computing: What are these algorithms actually trained on?

In the machine learning research community, significant importance is given to the optimization of techniques which are employed once a benchmark dataset is given. However, less importance is assigned to the quality of these datasets and to how these datasets are obtained. In this work, we look into annotation practices in the research area of...

The Effect of Temporal Supervision on the Prediction of Self-reported Emotion from Behavioural Features

Continuous affective self-reports are intrusive and expensive to acquire, forcing researchers to use alternative labels for the construction of their predictive models. The most predominantly used labels in literature are continuous perceived affective labels obtained using external annotators. However an increasing body of research indicates...