2017
A transfer learning and progressive stacking approach to reducing deep model sizes with an application to speech enhancement
ICASSP 2017accepted
Leveraging upon transfer learning, we distill the knowledge in a conventional wide and deep neural network (DNN) into a narrower yet deeper model with fewer parameters and comparable system performance for speech enhancement. We present three transfer-learning solutions to accomplish our goal. First…