Recovery of voice audio quality using a deep learning model

A wearable audio output device, comprising:

• at least one in-ear microphone acoustically coupled to an environment inside an ear canal of a user, the at least one in-ear microphone configured to receive an audio signal having a first frequency band;
• at least one processor and a memory coupled to the at least one in-ear microphone, the memory including instructions executable by the at least one processor to cause the wearable audio output device to:
• receive an external signal from an environment outside the ear canal of the user;
• determine the environment outside the ear of the user comprises a noisy environment by comparing a signal energy of the audio signal to a signal energy of the external signal;
• predict high-frequency band information for the audio signal using a model trained using training data of known high-frequency bands associated with low-frequency bands;
• and
• generate an output signal having a second frequency band based, at least in part, on the first frequency band of the audio signal and the predicted high-frequency band information for the audio signal;
• and
• at least one speaker coupled to the at least one in-ear microphone, the at least one speaker configured to:
• output the output signal having the second frequency band.

A computer-readable device storing instructions which when executed by at least one processor performs a method for recovering audio quality of voice when processing signals associated with a wearable audio output device, the method comprising:

• receiving, by an in-ear microphone acoustically coupled to an environment inside an ear canal of a user, an audio signal having a first frequency band;
• receiving an external signal from an environment outside the ear canal of the user;
• determining the environment outside the ear of the user comprises a noisy environment by comparing a signal energy of the audio signal to a signal energy of the external signal;
• predicting high-frequency band information for the audio signal using a model trained using training data of known high-frequency bands associated with low-frequency bands;
• generating an output signal having a second frequency band based, at least in part, on the first frequency band of the audio signal and the predicted high-frequency band information for the audio signal;
• and
• outputting, by the wearable audio output device, the output signal having the second frequency band.