Patent ID: 11929086
Assignee: ARIZONA BOARD OF REGENTS ON BEHALF OF ARIZONA STATE UNIVERSITY
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 13:
14. A method, comprising:
providing 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; and

providing the computer-implemented neural network based architecture with the input mixture, wherein the input mixture comprises a plurality of audio sources;
inferring a plurality of multi-scale audio features from the input mixture using the computer-implemented neural network based architecture; and
predicting constituent audio sources based on the plurality of inferred multi-scale audio features using the computer-implemented neural network based architecture.