Self-labeling with feature transfer for speech emotion recognition

for speech emotion recognition is designed and trained. As most speech emotion datasets are very small, the feature transfer model is applied to further enhance the performance of the SL learning method, which is trained on large-scale audio data. Experimental results on various datasets demonstrate the effectiveness of the proposed method.