Publication: Semi-supervised autoencoders for speech emotion recognition
Semi-supervised autoencoders for speech emotion recognition
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Deng, J., Xu, X., Zhang, Z., Frühholz, S., & Schuller, B. (2017). Semi-supervised autoencoders for speech emotion recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 99, 1–1. https://doi.org/10.1109/TASLP.2017.2759338
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Despite the widespread use of supervised learning methods for speech emotion recognition, they are severely restricted due to the lack of sufficient amount of labelled speech data for the training. Considering the wide availability of unlabelled speech data, therefore, this paper proposes semisupervised autoencoders to improve speech emotion recognition. The aim is to reap the benefit from the combination of the labelled data and unlabelled data. The proposed model extends a popular unsupervised autoencoder by carefully adjoining a su
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- Deng, Jun
- Xu, Xinzhou
- Zhang, Zixing
- Frühholz, Sascha
- Schuller, Bjorn
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Deng, J., Xu, X., Zhang, Z., Frühholz, S., & Schuller, B. (2017). Semi-supervised autoencoders for speech emotion recognition. IEEE/ACM Transactions on Audio, Speech, and Language Processing, 99, 1–1. https://doi.org/10.1109/TASLP.2017.2759338