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2010 – 2019
- 2014
[j1]Ingo Siegert, David Philippou-Hübner, Kim Hartmann, Ronald Böck, Andreas Wendemuth:
Investigation of Speaker Group-Dependent Modelling for Recognition of Affective States from Speech. Cogn. Comput. 6(4): 892-913 (2014)- 2013
- [c9]Bogdan Vlasenko, David Philippou-Hübner, Andreas Wendemuth:
Parameter Optimization Issues for Cross-corpora Emotion Classification. ACII 2013: 454-459 - [c8]Ingo Siegert, Kim Hartmann, David Philippou-Hübner, Andreas Wendemuth:
Human Behaviour in HCI: Complex Emotion Detection through Sparse Speech Features. HBU 2013: 246-257 - [c7]Kim Hartmann, Ingo Siegert, David Philippou-Hübner, Andreas Wendemuth:
Emotion Detection in HCI: From Speech Features to Emotion Space. IFAC HMS 2013: 288-295 - 2012
- [c6]David Philippou-Hübner, Bogdan Vlasenko, Ronald Böck, Andreas Wendemuth:
The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech. ICME 2012: 248-253 - [c5]David Philippou-Hübner, Bogdan Vlasenko, Ronald Böck, Andreas Wendemuth:
The Performance of the Speaking Rate Parameter in Emotion Recognition from Speech. ICME Workshops 2012: 296-301 - 2011
- [c4]Ingo Siegert, Ronald Böck, Bogdan Vlasenko, David Philippou-Hübner, Andreas Wendemuth:
Appropriate emotional labelling of non-acted speech using basic emotions, geneva emotion wheel and self assessment manikins. ICME 2011: 1-6 - [c3]Bogdan Vlasenko, David Philippou-Hübner, Dmytro Prylipko, Ronald Böck, Ingo Siegert, Andreas Wendemuth:
Vowels formants analysis allows straightforward detection of high arousal emotions. ICME 2011: 1-6 - [c2]Bogdan Vlasenko, Dmytro Prylipko, David Philippou-Hübner, Andreas Wendemuth:
Vowels Formants Analysis Allows Straightforward Detection of High Arousal Acted and Spontaneous Emotions. INTERSPEECH 2011: 1577-1580 - 2010
- [c1]David Philippou-Hübner, Bogdan Vlasenko, Tobias Grosser, Andreas Wendemuth:
Determining optimal features for emotion recognition from speech by applying an evolutionary algorithm. INTERSPEECH 2010: 2358-2361
Coauthor Index
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