An Efficient Language-Independent Acoustic Emotion Classification System
Author:
Funder
DIC Project MHRD
Publisher
Springer Science and Business Media LLC
Subject
Multidisciplinary
Link
http://link.springer.com/content/pdf/10.1007/s13369-019-04293-9.pdf
Reference46 articles.
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2. Scherer, K.R.: Vocal communication of emotion: a review of research paradigms. Speech Commun. 40(1–2), 227–256 (2003)
3. Cao, H.; Cooper, D.G.; Keutmann, M.K.; Gur, R.C.; Nenkova, A.; Verma, R.: ‘CREMA-D’: crowd-sourced emotional multimodal actors dataset. IEEE Trans. Affect. Comput. 5(4), 377–390 (2014)
4. Barsoum, E.; Zhang, C.; Ferrer, C.C., Zhang, Z.: Training deep networks for facial expression recognition with crowd-sourced label distribution. In: Proceedings of the 18th ACM International Conference on Multimodal Interaction, pp. 279–283. ACM (2016)
5. Abdelwahab, M.; Busso, C.: Study of dense network approaches for speech emotion recognition. In: 2018 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP), pp. 5084–5088. IEEE (2018)
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