End-to-end learning for dimensional emotion recognition from physiological signals
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Fabien Ringeval | Erik Marchi | Björn W. Schuller | Gil Keren | Tobias Kirschstein | Björn Schuller | F. Ringeval | Gil Keren | E. Marchi | Tobias Kirschstein
[1] Kuldip K. Paliwal,et al. Bidirectional recurrent neural networks , 1997, IEEE Trans. Signal Process..
[2] Pavel Matejka,et al. Multimodal Emotion Recognition for AVEC 2016 Challenge , 2016, AVEC@ACM Multimedia.
[3] Sergey Ioffe,et al. Batch Normalization: Accelerating Deep Network Training by Reducing Internal Covariate Shift , 2015, ICML.
[4] Daniel McDuff,et al. Advancements in Noncontact, Multiparameter Physiological Measurements Using a Webcam , 2011, IEEE Transactions on Biomedical Engineering.
[5] Dongmei Jiang,et al. Multimodal Affective Dimension Prediction Using Deep Bidirectional Long Short-Term Memory Recurrent Neural Networks , 2015, AVEC@ACM Multimedia.
[6] Bo Sun,et al. Exploring Multimodal Visual Features for Continuous Affect Recognition , 2016, AVEC@ACM Multimedia.
[7] Fabien Ringeval,et al. AV+EC 2015: The First Affect Recognition Challenge Bridging Across Audio, Video, and Physiological Data , 2015, AVEC@ACM Multimedia.
[8] Fabien Ringeval,et al. AVEC 2016: Depression, Mood, and Emotion Recognition Workshop and Challenge , 2016, AVEC@ACM Multimedia.
[9] N. Frijda,et al. Emotions and respiratory patterns: review and critical analysis. , 1994, International journal of psychophysiology : official journal of the International Organization of Psychophysiology.
[10] L. Lin,et al. A concordance correlation coefficient to evaluate reproducibility. , 1989, Biometrics.
[11] Daniel McDuff,et al. Biophone: Physiology monitoring from peripheral smartphone motions , 2015, 2015 37th Annual International Conference of the IEEE Engineering in Medicine and Biology Society (EMBC).
[12] Thomas S. Huang,et al. How deep neural networks can improve emotion recognition on video data , 2016, 2016 IEEE International Conference on Image Processing (ICIP).
[13] C. Nickerson. A note on a concordance correlation coefficient to evaluate reproducibility , 1997 .
[14] Fabien Ringeval,et al. Continuous Estimation of Emotions in Speech by Dynamic Cooperative Speaker Models , 2017, IEEE Transactions on Affective Computing.
[15] Björn W. Schuller,et al. Automatic multi-lingual arousal detection from voice applied to real product testing applications , 2017, 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[16] George Trigeorgis,et al. Adieu features? End-to-end speech emotion recognition using a deep convolutional recurrent network , 2016, 2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[17] Patrick Thiam,et al. Ensemble Methods for Continuous Affect Recognition: Multi-modality, Temporality, and Challenges , 2015, AVEC@ACM Multimedia.
[18] Murtaza Bulut,et al. Mobile real-time arousal detection , 2014, 2014 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP).
[19] Renaud Séguier,et al. High-Level Geometry-based Features of Video Modality for Emotion Prediction , 2016, AVEC@ACM Multimedia.
[20] Qin Jin,et al. Multi-modal Dimensional Emotion Recognition using Recurrent Neural Networks , 2015, AVEC@ACM Multimedia.
[21] Jean-Philippe Thiran,et al. Prediction of asynchronous dimensional emotion ratings from audiovisual and physiological data , 2015, Pattern Recognit. Lett..
[22] Matthew D. Zeiler. ADADELTA: An Adaptive Learning Rate Method , 2012, ArXiv.
[23] Nitish Srivastava,et al. Dropout: a simple way to prevent neural networks from overfitting , 2014, J. Mach. Learn. Res..
[24] M. Bradley,et al. The pupil as a measure of emotional arousal and autonomic activation. , 2008, Psychophysiology.
[25] Fabien Ringeval,et al. Introducing the RECOLA multimodal corpus of remote collaborative and affective interactions , 2013, 2013 10th IEEE International Conference and Workshops on Automatic Face and Gesture Recognition (FG).
[26] Anja Bachmann,et al. Leveraging smartwatches for unobtrusive mobile ambulatory mood assessment , 2015, UbiComp/ISWC Adjunct.
[27] Björn W. Schuller,et al. Automatic recognition of physiological parameters in the human voice: Heart rate and skin conductance , 2013, 2013 IEEE International Conference on Acoustics, Speech and Signal Processing.
[28] Fabien Ringeval,et al. Discriminatively Trained Recurrent Neural Networks for Continuous Dimensional Emotion Recognition from Audio , 2016, IJCAI.
[29] Jürgen Schmidhuber,et al. Long Short-Term Memory , 1997, Neural Computation.
[30] Lawrence D. Jackel,et al. Backpropagation Applied to Handwritten Zip Code Recognition , 1989, Neural Computation.
[31] Björn W. Schuller,et al. Convolutional Neural Networks with Data Augmentation for Classifying Speakers' Native Language , 2016, INTERSPEECH.
[32] R. Lazarus. Emotion and Adaptation , 1991 .