DNN-GRU Multiple Layers for VAD in PC Game Cafe

In this paper, we present multi-layer networks based on Deep Neural Networks (DNNs; also known as Dense layer or fully connected layer) and Gated Recurrent Units (GRUs) for Voice Activity Detection (VAD) with temporal smoothing in noisy PC game cafe environments. The noise from PC game cafe has distinctive features from previous VAD studies. To improve the accuracy of VAD in noisy environments, we recommend multi-layer neural networks with the fusion of DNNs and GRUs. DNNs were used as the first layer and last one because DNNs are good at mapping features and performing class-based discrimination. In order to take advantage of time sequence modeling such as speech, we used GRU We show that our model made better performance for the PC game cafe noisy environment compared to using only DNNs and GRUs.