Table 3.

Features of the selected emotion speech databases^a.

Database	Speakers	Emotions	Nature of material	Total stimuli
Anna (Hammerschmidt and Jürgens, 2007)	22 drama students (10 male/12 female)	Anger, affection, contempt, despair, fear, happiness, sensual satisfaction, triumph, neutral	Word	NStimuli = 198
Berlin Database of Emotional Speech (EMO_DB) (Burkhardt et al., 2005)	10 untrained actors (5 male/5 female)	Anger, boredom, disgust, fear, happiness, sadness, neutral	Semantic neutral sentences	NStimuli = 816
Magdeburg Prosody Corpus (WASEP) (Wendt and Scheich, 2002)	2 actors (1 male/1female)	Anger, disgust, fear, happiness, sadness, neutral	Pseudo-words Nounsb	NStimuli = 222 NStimuli = 3,318
Montreal Affective Voices (MAV) (Belin et al., 2008)	10 actors (5 male/5 female)	Anger, disgust, fear, happiness, pain, pleasure, sadness, surprise, neutral	Affect bursts	NStimuli = 90
Paulmann Prosodic Stimuli (Paulmann and Kotz, 2008; Paulmann et al., 2008)	2 actors (1 male/1female)	Anger, disgust, fear, happiness, sadness, surprise, neutral	Pseudo- sentences Lexical sentencesc	NStimuli = 210 NStimuli = 210

^aThe word databases it is used as a generic term as some of the selected stimuli are from researchers that developed their own stimulus materials with no aim of establishing a database (i.e., Anna and Paulmann prosodic stimuli).

^bThe nouns from WASEP are classified according to their positive, negative and neutral semantic content.

^cPaulmann lexical sentences consists of semantically and prosodically matching stimuli. Compared to all other types of stimuli, which were cross-over designed (i.e., stimulus is spoken in all emotional categories) both, the pseudo- and lexical sentences from Paulmann et al. (2008) database were hierarchically designed (i.e., stimulus is spoken only in one emotional category). The validation procedures of the stimuli are presented in the above-cited papers.