Cross-Corpus Classification of Realistic Emotions - Some Pilot Experiments - Eyben, Florian; Batliner, Anton; Schuller, Björn; Seppi, Dino; Steidl, Stefan (Proc. of theThird International Workshop on EMOTION (satellite of LREC): CORPORA FOR RESEARCH ON EMOTION AND AFFECT, 2010)
We use four speech databases with realistic, non-prompted emotions, and a large state-of-the-art acoustic feature vector, for cross-corpus classifications, in turn employing three databases for training and the fourth for testing. Categorical and continuous (dimensional) annotation is mapped onto a representation of valence with the three classes positive, neutral, and negative. This cross-corpus classification is compared with within corpus classifications. We interpret performance and most important features.