What is my Dog Trying to Tell Me? the Automatic Recognition of the Context and Perceived Emotion of Dog Barks

A wide range of research disciplines are deeply interested in the measurement of animal emotions, including evolutionary zoology, affective neuroscience and comparative psychology. However, only a few studies have investigated the effect of phenomena such as emotion on the acoustic parameters of (non-human) mammalian species. In this contribution, we explore if commonly used affective computing-based acoustic feature sets can be used to classify either the context, the emotion, or predict the emotional intensity of dog bark sequences. This comparison study includes an in-depth analysis of obtainable classification performances. Results presented indicate that the tested feature representations are suitable for the proposed recognition tasks. Of particular note are results that demonstrate machine learning-based acoustic analysis can achieve above human level performance when classifying the context of a dog bark.