Aiming at problem of low mask speech recognition rate of noise mask speech

mask speech recognition method based on improved convolutional neural network（ CNN） is proposed. Combine speech enhancement algorithm to suppress noise of mask speech and increase signal-to-noise ratio（ SNR）. An improved Wiener filtering algorithm is proposed for speech enhancement. Using spectral entropy algorithm to detect the frame which has speech to update noise power spectrum. At the same time

introducing parameter β to control gain function. Extract Mel frequency cepstrum coefficient（ MFCC） as characteristic parameters. Use CNN for training and recognization. The CNN includes two convolution layers

two pooling layers

one fully connected layer and a softmax classifier. And add local response normalization（ LRN） after every pooling layer to optimize CNN. The experimental results show that the recognition system can greatly improve the recognition rate of noisy mask speech.