EAR-WORN ELECTRONIC DEVICE EMPLOYING ACOUSTIC ENVIRONMENT ADAPTATION

1 . An ear-worn electronic device configured to be worn in, on or about an ear of a wearer, comprising:

at least one microphone configured to sense sound in an acoustic environment;

an acoustic transducer;

a non-volatile memory configured to store a plurality of parameter value sets, each of the parameter value sets associated with a different acoustic environment;

a control input configured to receive a control input signal produced by at least one of a user-actuatable control of the ear-worn electronic device and an external electronic device communicatively coupled to the ear-worn electronic device in response to a user action; and

a processor operably coupled to the microphone, the acoustic transducer, the non-volatile memory, and the control input, the processor configured to classify the acoustic environment using the sensed sound and apply, in response to the control input signal, one of the parameter value sets appropriate for the classification.

2 . The device according to claim 1 , wherein:

the user-actuatable control comprises one or more of a button disposed on the device, a sensor responsive to a touch or a tap by the wearer, a voice recognition control implemented by the processor, and gesture detection circuitry responsive to a wearer gesture made in proximity to the device; and

the external electronic device communicatively coupled to the ear-worn electronic device comprises one or more of a personal digital assistant, a smartphone, a smart watch, a tablet, and a laptop.

3 . The device according to claim 1 , wherein each of the parameter value sets comprises a set of gain values or gain offsets associated with a different acoustic environment, and one or both of:

a set of noise-reduction parameters associated with the different acoustic environments; and

a set of microphone mode parameters associated with the different acoustic environments.

4 . The device according to claim 1 , wherein the parameter value sets comprise:

a normal parameter value set associated with a normal or default acoustic environment;

a plurality of other parameter value sets each associated with a different acoustic environment; and

each of the other parameter value sets defines offsets to parameters of the normal parameter value set.

5 . The device according to claim 1 , comprising:

a sensor arrangement comprising one or more sensors configured to sense, and produce sensor signals indicative of, one or more of a physical state, a physiologic state, and an activity status of the wearer; and

the processor is configured to receive the sensor signals, classify the acoustic environment using the sensed sound, and apply, in response to the control input, one of the parameter value sets appropriate for the classification and one or more of the physical state, the physiologic state, and the activity status of the wearer.

6 . The device according to claim 5 , wherein the one or more sensors comprise one or both of a motion sensor and a physiologic sensor.

7 . The device according to claim 1 , wherein the processor is configured to apply one of the parameter value sets that enhance intelligibility of speech in the acoustic environment.

8 . The device according to claim 1 , wherein the acoustic environment includes muffled speech, and the processor is configured to:

classify the acoustic environment as an acoustic environment including muffled speech using the sensed sound; and

apply a parameter value set that enhances intelligibility of muffled speech.

9 . The device according to claim 1 , wherein, subsequent to applying an initial parameter value set appropriate for an initial classification of a current acoustic environment in response to receiving an initial control input signal, the processor is configured to:

automatically apply an adapted parameter value set appropriate for the initial or a subsequent classification of the current acoustic environment in the absence of receiving a subsequent control input signal by the processor.

10 . The device according to claim 1 , wherein the processor is configured to:

apply one or more different parameter value sets appropriate for the classification of a current acoustic environment in response to one or more subsequently received control input signals;

learn wearer preferences using utilization data acquired during application of the different parameter value sets by the processor; and

adapt selection of subsequent parameter value sets by the processor for subsequent use in the current acoustic environment using the learned wearer preferences.

11 . The device according to claim 1 , wherein the processor is configured to:

apply one or more different parameter value sets appropriate for the classification of a current acoustic environment in response to one or more subsequently received control input signals;

store, in the memory, one or both of utilization data and contextual data acquired by the processor during application of the different parameter value sets associated with the current acoustic environment; and

adapt selection of subsequent parameter value sets by the processor for subsequent use in the current acoustic environment using one or both of the utilization data and the contextual data.

12 . The device according to claim 1 , wherein the processor is configured with instructions to implement a machine learning algorithm to:

automatically apply an adapted parameter value set appropriate for an initial or a subsequent classification of a current acoustic environment.

13 . A method implemented by an ear-worn electronic device configured to be worn in, on or about an ear of a wearer, the method comprising:

storing a plurality of parameter value sets in non-volatile memory of the device, each of the parameter value sets associated with a different acoustic environment;

sensing sound in an acoustic environment;

classifying, by a processor of the device, the acoustic environment using the sensed sound;

receiving, by the processor, a control input signal produced by at least one of a user-actuatable control of the device and an external electronic device communicatively coupled to the device in response to a user action; and

applying, by the processor in response to the control input signal, one of the parameter value sets appropriate for the classification.

14 . The method according to claim 13 , comprising:

sensing, using a sensor arrangement of the device, one or more of a physical state, a physiologic state, and an activity status of the wearer;

producing, by the sensor arrangement, sensor signals indicative of one or more of the physical state, the physiologic state, and the activity status of the wearer; and

applying, by the processor in response to the control input signal, one of the parameter value sets appropriate for the classification and one or more of the physical state, the physiologic state, and the activity status of the wearer.

15 . The method according to claim 13 , wherein the processor is configured to apply one of the parameter value sets that enhance intelligibility of speech in the acoustic environment.

16 . The device according to claim 1 , wherein the processor is configured with instructions to implement a machine learning algorithm to learn wearer preferences using utilization data acquired during application of different parameter value sets applied by the processor.

17 . The device according to claim 16 , wherein the processor is configured with instructions to implement a machine learning algorithm to adapt selection of subsequent parameter value sets by the processor for subsequent use in a current acoustic environment using learned wearer preferences.

18 . The device according to claim 16 , wherein the processor is configured with instructions to implement a machine learning algorithm to adapt selection of subsequent parameter value sets for subsequent use in a current acoustic environment using the utilization data and contextual data.

19 . The method according to claim 13 , wherein the acoustic environment includes muffled speech, and the method comprises:

classifying the acoustic environment as an acoustic environment including muffled speech using the sensed sound; and

applying a parameter value set that enhances intelligibility of muffled speech.

20 . The method according to claim 13 , wherein, subsequent to applying an initial parameter value set appropriate for an initial classification of a current acoustic environment in response to receiving an initial control input signal, the method comprises:

automatically applying an adapted parameter value set appropriate for the initial or a subsequent classification of the current acoustic environment in the absence of receiving a subsequent control input signal by the processor.

21 . The method according to claim 13 , comprising:

applying one or more different parameter value sets appropriate for the classification of a current acoustic environment in response to one or more subsequently received control input signals;

learning wearer preferences using utilization data acquired during application of the different parameter value sets by the processor; and

adapting selection of subsequent parameter value sets by the processor for subsequent use in the current acoustic environment using the learned wearer preferences.

22 . The method according to claims 13 , comprising:

applying one or more different parameter value sets appropriate for the classification of a current acoustic environment in response to one or more subsequently received control input signals;

storing, in the memory, one or both of utilization data and contextual data acquired by the processor during application of the different parameter value sets associated with the current acoustic environment; and

adapting selection of subsequent parameter value sets by the processor for subsequent use in the current acoustic environment using one or both of the utilization data and the contextual data.