SPEECH ENHANCEMENT METHOD BASED ON FULLY CONVOLUTIONAL NEURAL NETWORK, DEVICE, AND STORAGE MEDIUM

摘要

The present application relates to the field of artificial intelligence. Disclosed is a speech enhancement method based on a fully convolutional neural network. The method comprises: constructing a fully convolutional neural network model, the fully convolutional neural network comprising an input layer, a hidden layer, and an output layer; the hidden layer comprising a plurality of convolutional layers; each of the plurality of convolutional layers comprising a plurality of filters; training the fully convolutional neural network model; inputting an original speech signal into the trained fully convolutional neural network model; and outputting an enhanced speech signal. In the fully convolutional neural network model of the present application, a full connection layer is deleted, and only convolutional layers are comprised, so that parameters of the neural network are significantly reduced, the fully convolutional neural network model can be suitable for a mobile device having the memory limited, each output sample only relies on adjacent inputs, and original information and spatial arrangement information of the speech signal can be reserved well at less weight values. Also disclosed are an electronic device and a computer readable storage medium.