Methods for neural network-based voice enhancement and systems thereof

A method, comprising:

• training a first neural network using input audio training data and a second neural network using a target speech sample and low-dimensional representations of input audio training data speech frames,
• applying the first neural network to convert input speech frames fragmented from input audio data to other low-dimensional representations of the input speech frames that omit non- content elements of the input audio data;
• applying the second neural network to the other low-dimensional representations to generate target speech frames;
• and
• combining the target speech frames to generate output audio data comprising foreground speech content and speech characteristics of the input audio data.

A non-transitory computer-readable medium comprising instructions that, when executed by one or more processors, cause the one or more processors to:

• digitize analog input audio signals to generate input audio data;
• fragment the input audio data into a plurality of input speech frames;
• convert the input speech frames to low-dimensional representations of the input speech frames based on an application of one or more neural networks to the input audio data, wherein the low-dimensional representations omit one or more of non-content elements in the input audio data;
• apply the one or more neural networks to the low-dimensional representations to generate target speech frames;
• combine the target speech frames to generate output audio data comprising foreground speech content or the speech characteristics in the input audio data;
• and
• convert the output audio data to analog audio output signals before providing the analog audio output signals to an audio output device.