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Modeling subjectiveness in emotion recognition with deep neural networks: Ensembles vs soft labels.

, , and . IJCNN, page 566-570. IEEE, (2016)

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Recognition of stress in speech using wavelet analysis and Teager energy operator., , , and . INTERSPEECH, page 605-608. ISCA, (2008)Optimization of a temporal decomposition model of speech., , and . ISSPA, page 471-474. IEEE, (1999)Modeling subjectiveness in emotion recognition with deep neural networks: Ensembles vs soft labels., , and . IJCNN, page 566-570. IEEE, (2016)Speaker Verification Based on Different Vector Quantization Techniques with Gaussian Mixture Models., , and . NSS, page 403-408. IEEE Computer Society, (2009)Evaluating deep learning architectures for Speech Emotion Recognition., , and . Neural Networks, (2017)Multichannel Weighted Speech Classification System for Prediction of Major Depression in Adolescents., , and . IEEE Trans. Biomed. Engineering, 60 (2): 497-506 (2013)Statistical differences in speech acoustics of major depressed and non-depressed adolescents., , and . ICSPCS, page 1-7. IEEE, (2015)Sleep Stage Recognition from EEG Using a Distributed Multi-Channel Decision-Making System., , and . ICSPCS, page 1-7. IEEE, (2021)Averaged Gabor Filter Features for Facial Expression Recognition., and . DICTA, page 71-76. IEEE Computer Society, (2008)Using information theoretic vector quantization for GMM based speaker verification., and . EUSIPCO, page 1-5. IEEE, (2008)