Patent ID: 11930323
Assignee: LISTEN AND BE HEARD LLC
Field: Audio-visual technology (Electrical engineering)
Classification: CPC H  G | IPC G  H

Claim 12:
13. The system of claim 8, wherein the system further comprises a GPS sensor and camera coupled to the at least one processor, wherein the least one processor is further configured to:
display a menu comprising a plurality of power conservation modes associated with the tuning profiles within the graphical user interface, wherein the menu of power conservation modes includes a full AI mode;
execute a routine wherein the full AI mode is used to select the tuning profile used for altering of the input signal in the frequency domain out of the plurality of tuning profiles, wherein the processor amplifies the input signal according to the selected tuning profile, wherein to execute the routine the at least one processor is configured to:
sense a sound wave from a snapshot in current time from one of a microphone in the earpiece worn by the user or an external microphone;
average, sound waves sensed from a snapshot in current time in regular or irregular intervals for a cumulative sound wave snapshot over time;
sense a current location based on the GPS sensor;
capture an image from the camera;
select a tuning profile out of the plurality of tuning profiles according to a first time-based metric comparing, by the at least one processor, the sensed cumulative sound wave snapshot over time to a history of previously stored cumulative sound wave snapshots at various times;
select a tuning profile out of the plurality of tuning profiles according to a second location-based metric comparing the currently sensed location to a history of previously marked distances at different times, wherein each previously marked distance is associated with a particular tuning profile out of the plurality of tuning profiles;
select a tuning profile out of the plurality of tuning profiles according to a third image-based metric comparing a currently captured image from the connected camera to a history of past images taken from the same camera at various timepoints; and
input the selected tuning profiles from the first time-based metric, the second location-based metric, and the third image-based metric as further inputs into a neural network, and select the tuning profile to use for sound modulation based on the output of the neural network.