No sir Not weight but the resultant output after activation function, Maybe similar to transfer learning. For example, a pre-trained network is used first to fine-tune the model, then the second last layer output needs to be saved for further classification using SVM  or HMM etc.
I am following this paper

  

      ieeexplore.ieee.org
  

  
    

Speech Emotion Recognition Using Deep Convolutional Neural Network and...

  Speech emotion recognition is challenging because of the affective gap between the subjective emotions and low-level features. Integrating multilevel feature learning and model training, deep convolutional neural networks (DCNN) has exhibited...


  

  
    
    
  

  


Regards