Andreas Wendemuth
Andreas Wendemuth
Professor for Cognitive Systems, University Magdeburg
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Cited by
Cited by
Cross-corpus acoustic emotion recognition: Variances and strategies
B Schuller, B Vlasenko, F Eyben, M Wöllmer, A Stuhlsatz, A Wendemuth, ...
IEEE Transactions on Affective Computing 1 (2), 119-131, 2010
Acoustic emotion recognition: A benchmark comparison of performances
B Schuller, B Vlasenko, F Eyben, G Rigoll, A Wendemuth
2009 IEEE Workshop on Automatic Speech Recognition & Understanding, 552-557, 2009
Frame vs. turn-level: emotion recognition from speech considering static and dynamic processing
B Vlasenko, B Schuller, A Wendemuth, G Rigoll
International Conference on Affective Computing and Intelligent Interaction …, 2007
A companion technology for cognitive technical systems
A Wendemuth, S Biundo
Cognitive behavioural systems, 89-103, 2012
Combining frame and turn-level information for robust recognition of emotions within speech
B Vlasenko, B Schuller, A Wendemuth, G Rigoll
Proc. INTERSPEECH 2007, Antwerp, Belgium, 2007
Inter-rater reliability for emotion annotation in human–computer interaction: comparison and methodological improvements
I Siegert, R Böck, A Wendemuth
Journal on Multimodal User Interfaces 8 (1), 17-28, 2014
Speech recognition with support vector machines in a hybrid system.
SE Krüger, M Schafföner, M Katz, E Andelic, A Wendemuth
Interspeech, 993-996, 2005
Large vocabulary continuous speech recognition of Broadcast News–The Philips/RWTH approach
P Beyerlein, X Aubert, R Haeb-Umbach, M Harris, D Klakow, ...
Speech Communication 37 (1-2), 109-131, 2002
Companion-technology for cognitive technical systems
S Biundo, A Wendemuth
KI-Künstliche Intelligenz 30 (1), 71-75, 2016
Grundlagen der stochastischen Sprachverarbeitung
A Wendemuth, E Andelic, S Barth, S Dobler, M Katz, S Krüger, M Maiwald, ...
Grundlagen der stochastischen Sprachverarbeitung, 2009
Appropriate emotional labelling of non-acted speech using basic emotions, geneva emotion wheel and self assessment manikins
I Siegert, R Böck, B Vlasenko, D Philippou-Hübner, A Wendemuth
2011 IEEE International Conference on Multimedia and Expo, 1-6, 2011
Modeling phonetic pattern variability in favor of the creation of robust emotion classifiers for real-life applications
B Vlasenko, D Prylipko, R Böck, A Wendemuth
Computer Speech & Language 28 (2), 483-500, 2014
Advances in confidence measures for large vocabulary
A Wendemuth, G Rose, JGA Dolfing
1999 IEEE International Conference on Acoustics, Speech, and Signal …, 1999
Comparing one and two-stage acoustic modeling in the recognition of emotion in speech
B Schuller, B Vlasenko, R Minguez, G Rigoll, A Wendemuth
2007 IEEE Workshop on Automatic Speech Recognition & Understanding (ASRU …, 2007
Combining speech recognition and acoustic word emotion models for robust text-independent emotion recognition
B Schuller, B Vlasenko, D Arsic, G Rigoll, A Wendemuth
2008 IEEE International Conference on Multimedia and Expo, 1333-1336, 2008
Vowels formants analysis allows straightforward detection of high arousal acted and spontaneous emotions
B Vlasenko, D Prylipko, D Philippou-Hübner, A Wendemuth
Twelfth Annual Conference of the International Speech Communication Association, 2011
Mixture of support vector machines for hmm based speech recognition
SE Kruger, M Schaffoner, M Katz, E Andelic, A Wendemuth
18th International Conference on Pattern Recognition (ICPR'06) 4, 326-329, 2006
Combination of confidence measures in isolated word recognition.
JGA Dolfing, A Wendemuth
ICSLP, 1998
Grundlagen der digitalen Signalverarbeitung: ein mathematischer Zugang
A Wendemuth
Springer-Verlag, 2006
Towards emotion and affect detection in the multimodal last minute corpus
J Frommer, B Michaelis, D Rösner, A Wendemuth, R Friesen, M Haase, ...
Challenge 58, 8.6, 2012
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