Prosodic cues for perceptual task-oriented Human-H

This paper addresses the question of perceptual detection and prosodic cues analysis of emotional behavior in a spontaneous speech corpus of real Human-Human dialogs. Detecting real emotions should be a clear focus for research on modeling human dialog, as it could help with analyzing the evolution of the dialog. Our aims are to define appropriate emotions for call center services, to validate the presence of emotions via perceptual tests and to find robust cues for emotion detection. Most research has focused mainly on artificial data in which predefined-emotions were simulated by actors. For real-life corpora a set of appropriate emotion labels must be determined. To this purpose, we conducted a perceptual test exploring 2 experimental conditions: with and without the capacity of listening the audio-signal. Perceived emotions reflect the presence of shaded and mixed emotions/attitudes. We report correlations between objective values and both perceived prosodic parameters and emotion labels.