Adding center loss to softmax cross-entropy improves speech emotion recognition accuracy by 3 to 4 percent on IEMOCAP for both Mel and STFT spectrogram inputs.
The 2-D PCA embedding illustrated the discriminative power when using center loss, which enables the neural network to learn more effective fea- tures for SER
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learning discriminative features from spectrograms using center loss for speech emotion recognition
Adding center loss to softmax cross-entropy improves speech emotion recognition accuracy by 3 to 4 percent on IEMOCAP for both Mel and STFT spectrogram inputs.