Affective speaker state analysis in the presence of reverberation
International Journal of Speech Technology
A multitask approach to continuous five-dimensional affect sensing in natural speech
ACM Transactions on Interactive Intelligent Systems (TiiS) - Special Issue on Affective Interaction in Natural Environments
Classification of emotional speech using 3DEC hierarchical classifier
Speech Communication
Paralinguistics in speech and language-State-of-the-art and the challenge
Computer Speech and Language
On the development of an automatic voice pleasantness classification and intensity estimation system
Computer Speech and Language
Improving generalisation and robustness of acoustic affect recognition
Proceedings of the 14th ACM international conference on Multimodal interaction
Ten recent trends in computational paralinguistics
COST'11 Proceedings of the 2011 international conference on Cognitive Behavioural Systems
Compensating for speaker or lexical variabilities in speech for emotion recognition
Speech Communication
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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 preselected prototypical data, and true speaker disjunctive partitioning is still less common than simple cross-validation. Even speaker disjunctive evaluation can give only a little insight into the generalization ability of today's emotion recognition engines since training and test data used for system development usually tend to be similar as far as recording conditions, noise overlay, language, and types of emotions are concerned. A considerably more realistic impression can be gathered by interset evaluation: We therefore show results employing six standard databases in a cross-corpora evaluation experiment which could also be helpful for learning about chances to add resources for training and overcoming the typical sparseness in the field. To better cope with the observed high variances, different types of normalization are investigated. 1.8 k individual evaluations in total indicate the crucial performance inferiority of inter to intracorpus testing.