End-to-end voice enhancement method based on generation of countermeasure network

The invention discloses an end-to-end voice enhancement method based on generation of a countermeasure network. The method comprises the following steps of directly inputting a noisy voice signal intoa pre-trained deep neural network for signal processing and outputting an enhanced voice signal, wherein the depth neural network is obtained through training by the following steps of S1, preliminarily training to generate a countermeasure network, wherein the generation of the countermeasure network comprises two deep neural networks: a generator G and a discriminator D; S2, performing knowledge distillation on the simulated noisy voice through a traditional statistical speech enhancement algorithm, and then training to generate a countermeasure network again; S3, performing fine adjustmenton the generator G obtained through training through the real noisy voice; and S4, outputting the generator G trained in the above step as a final deep neural network for voice enhancement processing. 本发明公开了一种基于生成对抗网络的端到端语音增强