Auditory devices for hearing protection

An auditory device comprising:

• one or more processors;
• and
• logic encoded in one or more non-transitory media for execution by the one or more processors and when executed are operable to:
• monitor background noise to identify an ambient noise condition;
• determining that the background noise includes one or more frequencies that exceed a threshold frequency;
• output a determination that one or more presets correspond to the ambient noise condition, wherein the determination that the one or more presets correspond to the ambient noise condition is performed by a machine-learning model and the machine-learning model is trained by:
• providing training data that includes different ambient noise conditions, information about how the different ambient noise conditions change as a function of time, and a set of presets that reduce or block the background noise associated with the different ambient noise conditions;
• generating feature embeddings from the training data that group features of the different noise conditions based on similarity;
• providing training ambient noise conditions as input to the machine-learning model;
• outputting one or more training presets that correspond to each training ambient noise condition;
• comparing the one or more training presets to groundtruth data;
• and
• modifying parameters of the machine-learning model based on a loss function that identifies a difference of the one or more training presets to the groundtruth data;
• and
• apply the one or more presets, wherein the one or more presets reduce or block the background noise associated with the ambient noise condition based on patterns associated with the ambient noise condition, and wherein applying the one or more presets comprises reducing or blocking the background noise corresponding to the one or more frequencies.