Embedded enablement for optimal gain-mask machine learning, audio channel-based signal enhancement

A method comprising:

• receiving a noisy audio signal from an audio receiver;
• passing the noisy audio signal through a deep neural network (DNN) model to generate a mask of a magnitude spectrogram of the noisy audio signal;
• retrieving a clean-only audio spectra and a noise-only spectra of one or more frequencies that exist within the noisy audio signal;
• generating, by a processing device, a loss function as a combination of the clean-only audio spectra multiplied by the mask and the noise-only spectra multiplied by the mask;
• and
• training, by the processing device, the DNN model while minimizing the loss function to generate a trained DNN model useable in audio noise suppression and dereverberation.

A non-transitory computer-readable storage medium storing instructions, which when executed, cause a processing device to perform operations comprising:

• receiving a noisy audio signal from an audio receiver;
• passing the noisy audio signal through a deep neural network (DNN) model to generate a mask of a magnitude spectrogram of the noisy audio signal;
• retrieving a clean-only audio spectra and a noise-only spectra of one or more frequencies that exist within the noisy audio signal;
• generating a loss function as a combination of the clean-only audio spectra multiplied by the mask and the noise-only spectra multiplied by the mask;
• and
• training the DNN model while minimizing the loss function to generate a trained DNN model useable in audio noise suppression and dereverberation.