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Speaker-Invariant Affective Representation Learning Via Adversarial Training

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IEEE ICASSP 2020 Virtual Conference May 2020

Representation learning for speech emotion recognition is challenging due to labeled data sparsity issue and lack of gold-standard references. In addition, there is much variability from input speech signals, human subjective perception of the signals and

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Speaker-Invariant Affective Representation Learning Via Adversarial Training

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Representation learning for speech emotion recognition is challenging due to labeled data sparsity issue and lack of gold-standard references. In addition, there is much variability from input speech signals, human subjective perception of the signals and