Packet loss concealment based on instantaneous phase deviation and deep neural network

In the case of packet loss for real-time speech communication, the speech quality will be seriously affected. In order to recover the lost speech information during transmission, this paper proposes a packet loss concealment (Packet Loss Concealment, PLC) based on instantaneous phase deviation (Instantaneous Phase Deviation, IPD) and deep neural network (Deep Neural Network, DNN). In the training stage, the log power spectrum (Log Power Spectrum, LPS) and IPD of the speech are used as the input feature of the DNN training for learning the mapping relationship from the received packets to the lost packets. In the reconstruction stage, the received packets are sent to the well trained DNN for recovering the lost packet. Experimental results prove that under different packet loss rates, the proposed algorithm can gain better performance than conventional LPS+DNN-based PLC method.