Wearable hearing assist device with artifact remediation

A method of generating a processed audio signal for a hearing assistance device in which the processed audio signal is intended to perceptually dominate a user auditory experience, the method comprising:

• processing an unprocessed audio signal received by the hearing assistance device, wherein the processing includes utilizing a machine learning (ML) system to generate an ML enhanced audio signal, wherein the ML enhanced audio signal includes sound artifacts introduced by the ML system;
• determining a mixing coefficient from an environmental noise assessment wherein the mixing coefficient dictates proportions of the unprocessed audio signal and the ML enhanced audio signal to remediate the sound artifacts;
• mixing the ML enhanced audio signal with the unprocessed audio signal using the mixing coefficient to generate the processed audio signal;
• and
• outputting the processed audio signal.

A hearing assistance device, comprising:

• at least one microphone for capturing an input signal;
• an active noise reduction (ANR) system configured to generate a noise reduced audio signal from the input signal;
• a machine learning (ML) system configured to process the noise reduced audio signal and generate an ML enhanced audio signal, wherein the ML enhanced audio signal includes sound artifacts introduced by the ML system;
• a mixing algorithm that determines a mixing coefficient based on an environmental noise assessment, wherein the mixing coefficient dictates proportions of the unprocessed audio signal and the ML enhanced audio signal to remediate the sound artifacts introduced by the ML system;
• a mixer configured to mix the ML enhanced audio signal with the input signal to generate a processed signal;
• and
• an electroacoustic transducer configured to output the processed signal.