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Speech Emotion Recognition (SER) refers to the recognition of human emotions from natural speech.
P. Gupta and N. Rajput, “Two-stream emotion recognition for call center monitoring,” in Proc. Interspeech 2007 , 2007, pp. 2241–2244
2007
Earlier work this paper cites.
C. Busso, M. Bulut, C.-C. Lee, A. Kazemzadeh, E. Mower Provost, S. Kim, J. Chang, S. Lee, and S. Narayanan, “Iemocap: Interactive emotional dyadic motion capture database,” Language Resources and Evaluation , vol. 42, pp. 335–359, 12 2008
2008
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X. Zhu and A. Goldberg, Introduction to Semi-Supervised Learning , 01 2009, vol. 3
2009
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M. El Ayadi, M. S. Kamel, and F. Karray, “Survey on speech emotion recognition: Features, classification schemes, and databases,” Pattern Recognition , vol. 44, no. 3, pp. 572–587, 2011
2011
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D.-H. Lee et al. , “Pseudo-label: The simple and efficient semi-supervised learning method for deep neural networks,” in Workshop on challenges in representation learning, ICML , vol. 3, no. 2, 2013
2013
Earlier work this paper cites.
K. Han, D. Yu, and I. Tashev, “Speech emotion recognition using deep neural network and extreme learning machine,” in Interspeech 2014
2014
Earlier work this paper cites.
2015
Earlier work this paper cites.
G. Hinton, O. Vinyals, and J. Dean, “Distilling the knowledge in a neural network,” 2015
2015
Earlier work this paper cites.
J. Lee and I. Tashev, “High-level feature representation using recurrent neural network for speech emotion recognition,” in Interspeech 2015 . ISCA - International Speech Communication Association, September
2015
Earlier work this paper cites.
2017
Earlier work this paper cites.
A. Vaswani, N. Shazeer, N. Parmar, J. Uszkoreit, L. Jones, A. N. Gomez, L. Kaiser, and I. Polosukhin, “Attention is all you need,” 2017
2017
Earlier work this paper cites.
J. Konečný, H. B. McMahan, F. X. Yu, P. Richtárik, A. T. Suresh, and D. Bacon, “Federated learning: Strategies for improving communication efficiency,” 2017
2017
Earlier work this paper cites.
H. B. McMahan, E. Moore, D. Ramage, S. Hampson, and B. A. y Arcas, “Communication-efficient learning of deep networks from decentralized data,” in AISTATS , 2017
2017
Earlier work this paper cites.
S. Mirsamadi, E. Barsoum, and C. Zhang, “Automatic speech emotion recognition using recurrent neural networks with local attention,” in 2017 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) , 2017, pp. 2227–2231
2017
Cited alongside, same era.
2017
Cited alongside, same era.
H.-J. Vögel, R. Troncy, B. Huet, M. Önen, A. Ksentini, J. Conradt, A. Adi, A. Zadorojniy, J. Terken, J. Beskow, A. Morrison, C. Süß, K. Eng, F. Eyben, S. Al Moubayed, S. Müller, T. Hubregtsen, V. Ghaderi, R. Chadowitz, and J. Härri, “Emotion-awareness for intelligent vehicle assistants: A research agenda,” 05 2018, pp. 11–15
2018
Cited alongside, same era.
T. Yang, G. Andrew, H. Eichner, H. Sun, W. Li, N. Kong, D. Ramage, and F. Beaufays, “Applied federated learning: Improving google keyboard query suggestions,” 2018
Y. Shi, Y. Wang, C. Wu, C. Fuegen, F. Zhang, D. Le, C.-F. Yeh, and M. L. Seltzer, “Weak-attention suppression for transformer based speech recognition,” 2020
2020
Later among the works it cites.
T. Li, A. K. Sahu, A. S. Talwalkar, and V. Smith, “Federated learning: Challenges, methods, and future directions,” IEEE Signal Processing Magazine , vol. 37, pp. 50–60, 2020
2020
Later among the works it cites.
A. Hard, K. Partridge, C. Nguyen, N. Subrahmanya, A. Shah, P. Zhu, I. L. Moreno, and R. Mathews, “Training keyword spotting models on non-iid data with federated learning,” 2020
2020
Later among the works it cites.
Y. Jin, X. Wei, Y. Liu, and Q. Yang, “Towards utilizing unlabeled data in federated learning: A survey and prospective,” 2020
2020
Later among the works it cites.
E. Arazo, D. Ortego, P. Albert, N. E. O’Connor, and K. McGuinness, “Pseudo-labeling and confirmation bias in deep semi-supervised learning,” in 2020 International Joint Conference on Neural Networks (IJCNN)
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2018
Cited alongside, same era.
P. Li, Y. Song, I. Mcloughlin, W. Guo, and L. Dai, “An attention pooling based representation learning method for speech emotion recognition,” 09 2018, pp. 3087–3091
2018
Cited alongside, same era.
2018
Cited alongside, same era.
A. Badshah, N. Rahim, N. Ullah, J. Ahmad, K. Muhammad, M. Lee, S. Kwon, and S. Baik, “Deep features-based speech emotion recognition for smart affective services,” Multimedia Tools and Applications , 2019
2019
Cited alongside, same era.
M. Merler, K.-N. C. Mac, D. Joshi, Q.-B. Nguyen, S. Hammer, J. Kent, J. Xiong, M. N. Do, J. R. Smith, and R. S. Feris, “Automatic curation of sports highlights using multimodal excitement features,” IEEE Transactions on Multimedia , vol. 21, no. 5, pp. 1147–1160, 2019
2019
Cited alongside, same era.
D. Leroy, A. Coucke, T. Lavril, T. Gisselbrecht, and J. Dureau, “Federated learning for keyword spotting,” 2019
2019
Cited alongside, same era.
2019
Cited alongside, same era.
A. Oliver, A. Odena, C. Raffel, E. D. Cubuk, and I. J. Goodfellow, “Realistic evaluation of deep semi-supervised learning algorithms,” 2019
2019
Cited alongside, same era.
L. Tarantino, P. N. Garner, and A. Lazaridis, “Self-attention for speech emotion recognition,” in INTERSPEECH , 2019
2019
Cited alongside, same era.
2020
Later among the works it cites.
2020
Later among the works it cites.
W. Jeong, J. Yoon, E. Yang, and S. J. Hwang, “Federated semi-supervised learning with inter-client consistency,” 2020
2020
Later among the works it cites.
Z. Long, L. Che, Y. Wang, M. Ye, J. Luo, J. Wu, H. Xiao, and F. Ma, “Fedsemi: An adaptive federated semi-supervised learning framework,” 2020
2020
Later among the works it cites.
2020
Later among the works it cites.
E. Lieskovska, M. Jakubec, R. Jarina, and M. Chmulik, “A review on speech emotion recognition using deep learning and attention mechanism,” Electronics , vol. 10, p. 1163, 05 2021
2021
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2021
Later among the works it cites.
L. Guo, L. Wang, C. Xu, J. Dang, E. S. Chng, and H. Li, “Representation learning with spectro-temporal-channel attention for speech emotion recognition,” in ICASSP 2021 , 2021, pp. 6304–6308
2021
Later among the works it cites.
S. Padi, S. O. Sadjadi, D. Manocha, and R. D. Sriram, “Improved speech emotion recognition using transfer learning and spectrogram augmentation,” 2021
2021
Later among the works it cites.