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Cascaded Convolutional Neural Network Architecture for Speech Emotion Recognition in Noisy Conditions
2021
Sensors
Convolutional neural networks (CNNs) are a state-of-the-art technique for speech emotion recognition. However, CNNs have mostly been applied to noise-free emotional speech data, and limited evidence is available for their applicability in emotional speech denoising. In this study, a cascaded denoising CNN (DnCNN)–CNN architecture is proposed to classify emotions from Korean and German speech in noisy conditions. The proposed architecture consists of two stages. In the first stage, the DnCNN
doi:10.3390/s21134399
pmid:34199027
fatcat:2zl4jzf4urcmfml4cbk6d6vaoy