CPC G10L 21/0308 (2013.01) [G06F 16/635 (2019.01); G06N 3/04 (2013.01); G06N 3/08 (2013.01); G10L 25/30 (2013.01)] | 18 Claims |
1. A system, comprising:
a computer-implemented neural-network based architecture, including:
a downstream path configured to receive an input mixture, the downstream path comprising:
a plurality of downstream convolutional blocks configured to learn a plurality of features of the input mixture, wherein each downstream convolutional block of the plurality of downstream convolutional blocks includes a plurality of downstream convolutional layers having exponentially varying dilation rates associated with each respective upstream convolutional layer of the plurality of downstream convolutional layers;
wherein a first convolutional layer of the first downstream convolutional block directly receives the input mixture; and
an upstream path in communication with the downstream path, the upstream path configured to output a plurality of source waveforms associated with the input mixture, the upstream path comprising:
a plurality of upstream convolutional blocks configured to learn a plurality of features of the input mixture, wherein each upstream convolutional block of the plurality of upstream convolutional blocks includes a plurality of upstream convolutional layers having exponentially varying dilation rates associated with each respective upstream convolutional layer of the plurality of upstream convolutional layers;
the input mixture being connected directly to a final convolutional layer by a skip connection;
wherein the plurality of upstream convolutional blocks are transposed relative to the plurality of downstream convolutional blocks.
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