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Cross-lingual speech emotion recognition (SER) is a crucial task for many real-world applications.
1907
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J. Deng, Z. Zhang, E. Marchi, and B. Schuller, “Sparse autoencoder-based feature transfer learning for speech emotion recognition,” in Affective Computing and Intelligent Interaction (ACII), 2013 Humaine Association Conference on . IEEE, 2013, pp. 511–516
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C. Parlak, B. Diri, and F. Gürgen, “A cross-corpus experiment in speech emotion recognition.” in SLAM@ INTERSPEECH , 2014, pp. 58–61
2014
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J. Deng, Z. Zhang, F. Eyben, and B. Schuller, “Autoencoder-based unsupervised domain adaptation for speech emotion recognition,” IEEE Signal Processing Letters , vol. 21, no. 9, pp. 1068–1072, 2014
2014
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G. Costantini, I. Iaderola, A. Paoloni, and M. Todisco, “Emovo corpus: an italian emotional speech database.” in LREC , 2014, pp. 3501–3504
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H. Sagha, J. Deng, M. Gavryukova, J. Han, and B. Schuller, “Cross lingual speech emotion recognition using canonical correlation analysis on principal component subspace,” in Acoustics, Speech and Signal Processing (ICASSP), 2016 IEEE International Conference on . IEEE, 2016, pp. 5800–5804
2016
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Y. Shinohara, “Adversarial multi-task learning of deep neural networks for robust speech recognition.” in INTERSPEECH . San Francisco, CA, USA, 2016, pp. 2369–2372
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A. Qayyum, S. Latif, and J. Qadir, “Quran reciter identification: A deep learning approach,” in 2018 7th International Conference on Computer and Communication Engineering (ICCCE) . IEEE, 2018, pp. 492–497
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F. Eyben, K. R. Scherer, B. W. Schuller, J. Sundberg, E. André, C. Busso, L. Y. Devillers, J. Epps, P. Laukka, S. S. Narayanan et al. , “The geneva minimalistic acoustic parameter set (gemaps) for voice research and affective computing,” IEEE Transactions on Affective Computing , vol. 7, no. 2, pp. 190–202, 2016
2016
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S. Latif, R. Rana, J. Qadir, A. Ali, M. A. Imran, and M. S. Younis, “Mobile health in the developing world: Review of literature and lessons from a case study,” IEEE Access , vol. 5, pp. 11 540–11 556, 2017
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S. Latif, J. Qadir, S. Farooq, and M. Imran, “How 5g wireless (and concomitant technologies) will revolutionize healthcare?” Future Internet , vol. 9, no. 4, p. 93, 2017
2017
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J. Deng, X. Xu, Z. Zhang, S. Frühholz, and B. Schuller, “Universum autoencoder-based domain adaptation for speech emotion recognition,” IEEE Signal Processing Letters , vol. 24, no. 4, pp. 500–504, 2017
2017
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S. Sun, B. Zhang, L. Xie, and Y. Zhang, “An unsupervised deep domain adaptation approach for robust speech recognition,” Neurocomputing , vol. 257, pp. 79–87, 2017
2017
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E. M. Albornoz and D. H. Milone, “Emotion recognition in never-seen languages using a novel ensemble method with emotion profiles,” IEEE Transactions on Affective Computing , vol. 8, no. 1, pp. 43–53, 2017
2017
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J. Deng, X. Xu, Z. Zhang, S. Frühholz, and B. Schuller, “Universum autoencoder-based domain adaptation for speech emotion recognition,” IEEE Signal Processing Letters , vol. 24, no. 4, pp. 500–504, April 2017
2017
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K. Bousmalis, N. Silberman, D. Dohan, D. Erhan, and D. Krishnan, “Unsupervised pixel-level domain adaptation with generative adversarial networks,” in Proceedings of the IEEE conference on computer vision and pattern recognition , 2017, pp. 3722–3731
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2018
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Q. Wang, W. Rao, S. Sun, L. Xie, E. S. Chng, and H. Li, “Unsupervised domain adaptation via domain adversarial training for speaker recognition,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 4889–4893
2018
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Z. Meng, J. Li, Z. Chen, Y. Zhao, V. Mazalov, Y. Gang, and B.-H. Juang, “Speaker-invariant training via adversarial learning,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 5969–5973
2018
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M. Abdelwahab and C. Busso, “Domain adversarial for acoustic emotion recognition,” IEEE/ACM Transactions on Audio, Speech, and Language Processing , vol. 26, no. 12, pp. 2423–2435, 2018
2018
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M. Neumann et al. , “Cross-lingual and multilingual speech emotion recognition on english and french,” in 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2018, pp. 5769–5773
2018
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2018
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S. Latif, A. Qayyum, M. Usman, and J. Qadir, “Cross lingual speech emotion recognition: Urdu vs. western languages,” in 2018 International Conference on Frontiers of Information Technology (FIT) . IEEE, 2018, pp. 88–93
2018
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R. Rana, S. Latif, R. Gururajan, A. Gray, G. Mackenzie, G. Humphris, and J. Dunn, “Automated screening for distress: A perspective for the future,” European journal of cancer care , p. e13033, 2019
2019
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2019
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H. Zhou and K. Chen, “Transferable positive/negative speech emotion recognition via class-wise adversarial domain adaptation,” in ICASSP 2019-2019 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) . IEEE, 2019, pp. 3732–3736
2019
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2019
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X. Li and M. Akagi, “Improving multilingual speech emotion recognition by combining acoustic features in a three-layer model,” Speech Communication , 2019
2019
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