Reduced latency streaming dynamic noise suppression using convolutional neural networks

Abstract

Techniques are provided for dynamic noise suppression. A methodology implementing the techniques according to an embodiment includes generating a magnitude spectrum and a phase spectrum of an input audio signal comprising speech and dynamic noise. The method also includes employing a temporal convolution network (TCN) to generate a separation mask based on the magnitude spectrum. The TCN comprises depth-wise (DW) convolution layers, each DW convolution layer including a state buffer to store a number of previous states of the associated DW convolution layer. The number of stored previous states is based on a dilation factor of the associated DW convolution layer. The method further includes multiplying the separation mask with the magnitude spectrum to separate the speech from the dynamic noise to obtain a denoised magnitude spectrum. The method further includes reconstructing the input audio signal with reduced dynamic noise based on the denoised magnitude spectrum and the phase spectrum.