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 IDV-HR 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.