In an interaction, it is well known that information is being exchanged which is meaningful beyond the pure context. Especially, intentional and emotional characteristics are essential to improve not only the relationship in a human-human interaction, but also to provide benefits to increase the understanding of the transmitted information. For technical systems it is favourable to detect and interpret these additional characteristics and to transfer appropriate knowledge to human-machine interactions. In particular, this enables an automatic recognition of emotions. In this paper, we focus on speech as the transmitting modality. Beyond the detection of the location and nature of emotional instances, automatic interpretation asks "if", "how", and "when" emotions change in an interaction. In the EmoGest corpus, providing human-human interactions with emotionally induced subjects, we analyse the subject's emotional evolution. For this, we investigate the utterances spoken at the beginning and at the end of particular sessions. Automatic emotion recognition from speech shows that in intra- and inter-individual evaluations, significant differences (at least p
['Ronald Böck', 'Ingo Siegert']
Recognising Emotional Evolution from Speech