The Relevance of Feature Type for the Automatic Classification of Emotional User States: Low Level Descriptors and Functionals

Schuller B, Batliner A, Seppi D, Steidl S, Vogt T, Wagner J, Devillers L, Vidrascu L, Amir N, Kessous L, Aharonson V (2007)


Publication Language: English

Publication Type: Conference contribution, Conference Contribution

Publication year: 2007

Original Authors: Schuller Björn, Batliner Anton, Seppi Dino, Steidl Stefan, Vogt Thurid, Wagner Johannes, Devillers Laurence, Vidrascu Laurence, Amir Noam, Kessous Loic, Aharonson Vered

Pages Range: 2253-2256

Conference Proceedings Title: Proceedings Interspeech

Event location: Antwerp BE

URI: http://www5.informatik.uni-erlangen.de/Forschung/Publikationen/2007/Schuller07-TRO.pdf

Abstract

In this paper, we report on classification results for emotional user states (4 classes, German database of children interacting with a pet robot). Six sites computed acoustic and linguistic features independently from each other, following in part different strategies. A total of 4244 features were pooled together and grouped into 12 low level descriptor types and 6 functional types. For each of these groups, classification results using Support Vector Machines and Random Forests are reported for the full set of features, and for 150 features each with the highest individual Information Gain Ratio. The performance for the different groups varies mostly between ≈50% and ≈60%.

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APA:

Schuller, B., Batliner, A., Seppi, D., Steidl, S., Vogt, T., Wagner, J.,... Aharonson, V. (2007). The Relevance of Feature Type for the Automatic Classification of Emotional User States: Low Level Descriptors and Functionals. In ISCA (Eds.), Proceedings Interspeech (pp. 2253-2256). Antwerp, BE.

MLA:

Schuller, Björn, et al. "The Relevance of Feature Type for the Automatic Classification of Emotional User States: Low Level Descriptors and Functionals." Proceedings of the Interspeech, Antwerp Ed. ISCA, 2007. 2253-2256.

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