Abstract
A computer-implemented method for speech emotion recognition is provided. According to this computer-implemented method, an emotion prediction corresponding to speech data is generated based on the speech data and a speech emotion recognition model without bias. The speech emotion recognition model without bias is trained by training a fairness-constrained adversarial network based on a labeled training set with known bias and a loss function. The fairness-constrained adversarial network includes a domain classifier for bias classification and the speech emotion recognition model. The loss function used for training the fairness-constrained adversarial network is positively related to a Wasserstein distance (WD) loss.