10. The method of claim 1 , wherein the one or more context aware processing parameters includes one or more stored global contextual states associated with one or more other users.
1. A method, comprising: receiving, at a processor, one or more context aware processing parameters and an ambient audio stream, wherein the ambient audio stream is transmitted from one or more active acoustic filters to the processor, wherein the one or more active acoustic filters are configured to convert ambient sound received by the one or more active acoustic filters into the ambient audio stream; identifying using a machine learning model one or more sound characteristics associated with the ambient audio stream, wherein the machine learning model is comprised of a first hierarchical level that is comprised of a plurality of first hierarchical level machine learning models configured to each identify a corresponding sound characteristic within the ambient audio stream, a second hierarchical level comprised of a second hierarchical level machine learning model configured to determine one or more real characteristics of the ambient audio stream based on an output of the plurality of first hierarchical level machine learning models, and a third hierarchical level that is comprised of a third hierarchical level machine learning model; determining using the third hierarchical level machine learning model of the machine learning model one or more actions to perform based on the one or more context aware processing parameters, the identified one or more real characteristics determined by the second hierarchical level machine learning model, and a corresponding recommendation metric associated with the one or more actions; and performing the one or more actions.