@inproceedings{SchullerVlasenkoEybenetal.2015, author = {Schuller, Bj{\"o}rn and Vlasenko, Bogdan and Eyben, Florian and W{\"o}llmer, Martin and Stuhlsatz, Andr{\´e} and Wendemuth, Andreas and Rigoll, Gerhard}, title = {Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies (Extended Abstract)}, series = {In Proc. 6th biannual Conference on Affective Computing and Intelligent Interaction (ACII 2015), AAAC,}, booktitle = {In Proc. 6th biannual Conference on Affective Computing and Intelligent Interaction (ACII 2015), AAAC,}, year = {2015}, abstract = {As the recognition of emotion from speech has matured to a degree where it becomes applicable in real-life settings, it is time for a realistic view on obtainable performances. Most studies tend to overestimation in this respect: acted data is often used rather than spontaneous data, results are reported on pre-selected prototypical data, and true speaker disjunctive partitioning is still less common than simple cross-validation. A considerably more realistic impression can be gathered by inter-set evaluation: we therefore show results employing six standard databases in a cross-corpora evaluation experiment. To better cope with the observed high variances, different types of normalization are investigated. 1.8k individual evaluations in total indicate the crucial performance inferiority of inter- to intra-corpus testing.}, language = {en} } @article{SchullerVlasenkoEybenetal.2010, author = {Schuller, Bjorn and Vlasenko, Bogdan and Eyben, Florian and Wollmer, Martin and Stuhlsatz, Andr{\´e} and Wendemuth, Andreas and Rigoll, Gerhard}, title = {Cross-Corpus Acoustic Emotion Recognition: Variances and Strategies}, series = {IEEE Transactions on Affective Computing}, volume = {1}, journal = {IEEE Transactions on Affective Computing}, number = {2}, publisher = {IEEE}, doi = {10.1109/t-affc.2010.8}, pages = {119 -- 131}, year = {2010}, language = {en} }