We focus in this paper on the detection of emotions collected in real-life context. In order to improve our emotional valence detection system, we have tested new voice quality features that are mainly used for speech synthesis or voice transformation: the relaxation coefficient (Rd) and the functions of phase distortion (FPD); but also usual voice quality features. Distributions of voice quality features across speakers, gender, age and emotions are shown over the IDVHR ecological corpus. Our results conclude that glottal and usual voice quality features are of interest for emotional valence detection even facing diverse kind of voices in ecological situations.

Index Terms: voice quality features, emotional valence detection, shape parameter, real-life data.