Systems and methods for neural network training via local target signal augmentation

Abstract

Provided herein is an integrated circuit for generating augmented training data, including a host processor configured to receive a signal stream. The integrated circuit also has a co-processor commutatively coupled to the host-processor includes a neural network with at least a first set of weights configured to identify one or more target signals from the signal stream received from the host processor. A plurality of augmentation tools are also accessible to the integrated circuit. Finally, the integrated circuit, coupled computing device or other suitable digital signal processor stores a plurality of the one or more identified target signals, and upon reaching a predetermined threshold of identified target signals, utilizes the plurality of augmentation tools to generate an extended set of target signals, and generates a second set of weights for the neural network based on the extended set of target signals generated by the augmentation tools.