Linked Source and Target Domain Subspace Feature Transfer Learning -- Exemplified by Speech Emotion Recognition

@article{Deng2014LinkedSA,
  title={Linked Source and Target Domain Subspace Feature Transfer Learning -- Exemplified by Speech Emotion Recognition},
  author={Jun Deng and Zixing Zhang and Bj{\"o}rn W. Schuller},
  journal={2014 22nd International Conference on Pattern Recognition},
  year={2014},
  pages={761-766}
}
The typical inherent mismatch between the test and training corpora and by that between 'target' and 'source' sets usually leads to significant performance downgrades. To cope with this, this study presents a feature transfer learning method using Denoising Auto encoders (DAEs) to build high order subspaces of the source and target corpora, where features in the source domain are transferred to the target domain by an additional neural network. To exemplify effectiveness of our approach, we… CONTINUE READING
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Speech Emotion Recognition Using Semi-supervised Learning with Ladder Networks

2018 First Asian Conference on Affective Computing and Intelligent Interaction (ACII Asia) • 2018
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Cross-corpus acoustic emotion recognition from singing and speaking: A multi-task learning approach

2016 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP) • 2016
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