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Raymond Brueckner
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2020 – today
- 2023
- [c12]Vinod Subramanian, Namhee Kwon, Raymond Brueckner, Nate Blaylock, Henry O'Connell, Luis Sierra, Clementina Ullman, Karen Hildebrand, Simon E. Laganiere:
Detecting Manifest Huntington's Disease Using Vocal Data. INTERSPEECH 2023: 5032-5036 - [c11]Raymond Brueckner, Misa Takegami, Namhee Kwon, Nate Blaylock, Vinod Subramanian, Eri Kiyoshige, Soshiro Ogata, Yuriko Nakaoku, Henry O'Connell, Kunihiro Nishimura:
Voice Technology to Identify Fatigue from Japanese Speech. SMM 2023 - 2022
- [i1]Tobias Oetermann, Pia S. C. Dautzenberg, Gudrun Mechthild Irmgard Voß, Christopher Brockmeier, Stefan Ladwig, Patrick Gebhard, Tanja Schneeberger, Markus Funk, Raymond Brueckner, Felix Schäfer, Norbert Helff, Andreas Gomer, Lutz Eckstein:
EMMI: Empathic Human-Machine Interaction for Establishing Trust in Automated Driving. CoRR abs/2204.06377 (2022) - 2020
- [b1]Raymond Brueckner:
Application of Deep Learning Methods in Computational Paralinguistics. Technical University of Munich, Germany, 2020
2010 – 2019
- 2018
- [j1]Florian Lingenfelser
, Johannes Wagner, Jun Deng, Raymond Brueckner, Björn W. Schuller
Asynchronous and Event-Based Fusion Systems for Affect Recognition on Naturalistic Data in Comparison to Conventional Approaches. IEEE Trans. Affect. Comput. 9(4): 410-423 (2018) - 2017
- [c10]Florian B. Pokorny
Earlier Identification of Children with Autism Spectrum Disorder: An Automatic Vocalisation-Based Approach. INTERSPEECH 2017: 309-313 - [c9]Raymond Brueckner, Maximilian Schmitt, Maja Pantic, Björn W. Schuller
Spotting Social Signals in Conversational Speech over IP: A Deep Learning Perspective. INTERSPEECH 2017: 2371-2375 - 2016
- [c8]George Trigeorgis, Fabien Ringeval, Raymond Brueckner, Erik Marchi, Mihalis A. Nicolaou, Björn W. Schuller
Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network. ICASSP 2016: 5200-5204 - 2014
- [c7]Raymond Brueckner, Björn W. Schuller:
Social signal classification using deep blstm recurrent neural networks. ICASSP 2014: 4823-4827 - 2013
- [c6]Raymond Brueckner, Björn W. Schuller
Hierarchical neural networks and enhanced class posteriors for social signal classification. ASRU 2013: 362-367 - 2012
- [c5]Raymond Brueckner, Björn W. Schuller:
Likability Classification - A Not so Deep Neural Network Approach. INTERSPEECH 2012: 290-293
2000 – 2009
- 2008
- [c4]Daniel Vásquez, Rainer Gruhn, Raymond Brueckner, Wolfgang Minker:
Comparing Linear Feature Space Transformations for Correlated Features. PIT 2008: 176-187 - 2006
- [c3]Daniel Willett, Franz Gerl, Raymond Brueckner:
Discriminatively Trained Context-Dependent Duration-Bigram Models for Korean Digit Recognition. ICASSP (1) 2006: 25-28 - [c2]Ying Sun, Daniel Willett, Raymond Brueckner, Rainer Gruhn, Dirk Bühler:
Experiments on Chinese speech recognition with tonal models and pitch estimation using the Mandarin speecon data. INTERSPEECH 2006 - [c1]Jochen Schwenninger, Raymond Brueckner, Daniel Willett, Marcus E. Hennecke:
Language Identification in Vocal Music. ISMIR 2006: 377-379
Coauthor Index
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