Instability Mitigation in an Active Noise Reduction (ANR) System Having a Hear-Through Mode
In one aspect a method that includes receiving an input signal captured by one or more first sensors associated with an active noise reduction (ANR) device, and processing the input signal using a first filter disposed in an ANR signal path to generate a first signal for an acoustic transducer of the ANR device. The input signal is processed in a pass-through signal path disposed in parallel with the ANR signal path to generate a second signal for the acoustic transducer, wherein the pass-through signal path allows a portion of the input signal to pass through to the acoustic transducer in accordance with a variable gain. One or more second sensors detect an existence of a condition likely to cause instability in the pass-through signal path, and in response, the variable gain is adjusted. A driver signal for the acoustic transducer is generated using an output based on the adjusted gain.
1 .- 20 . (canceled)
21 . A method, comprising:
receiving an input signal produced by one or more sensors;
detecting a condition likely to cause instability in a pass-through signal path, wherein the condition likely to cause instability in the pass-through signal path comprises a condition likely to cause coupling between an output of an acoustic transducer and at least one of the one or more sensors;
processing the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path to generate a signal for the pass-through signal path; and
generating a drive signal for the acoustic transducer based in part on the signal for the pass-through signal path.
22 . The method of claim 21 , wherein detecting the condition likely to cause instability in the pass-through signal path comprises processing at least one of the input signal produced by the one or more sensors or another signal produced by one or more other sensors with a machine learning model to predict a probability of an existence of the condition likely to cause instability in the pass-through signal path.
23 . The method of claim 21 , further comprising:
responsive to detecting the condition likely to cause instability in the pass-through signal path, training a machine learning model to predict a probability of an existence of the condition likely to cause instability in the pass-through signal path based on at least one of the input signal produced by the one or more sensors or another signal produced by one or more other sensors.
24 . The method of claim 21 , wherein the pass-through signal path is configured to allow at least a portion of the input signal to pass through to the acoustic transducer.
25 . The method of claim 24 , wherein the condition likely to cause instability in the pass-through signal path comprises a condition likely to cause coupling between the portion of the input signal passed through the pass-through signal path and the at least one of the one or more sensors.
26 . The method of claim 21 , wherein detecting the condition likely to cause instability in the pass-through signal path comprises detecting, using one or more second sensors, that an object is within a predetermined distance from at least one of the one or more sensors or the one or more second sensors.
27 . The method of claim 21 , wherein processing the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path comprises selecting a gain for the pass-through signal path based on the detected condition.
28 . The method of claim 21 , wherein processing the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path comprises selecting one or more coefficients for a filter disposed in the pass-through signal path based on the detected condition.
29 . The method of claim 21 , wherein processing the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path comprises disabling the pass-through signal path.
30 . The method of claim 21 , further comprising:
detecting that the condition likely to cause instability in the pass-through signal path is no longer in existence; and
responsive to detecting that the condition likely to cause instability in the pass-through signal path is no longer in existence, adjusting the processing associated with the pass-through signal path.
31 . The method of claim 21 , further comprising:
processing the input signal to generate a signal for an active noise reduction (ANR) signal path; and
generating the drive signal for the acoustic transducer based in part on the signal for the pass-through signal path and the signal for the ANR signal path.
32 . A device, comprising:
an acoustic transducer;
one or more sensors configured to generate an input signal indicative of an external environment of the device;
one or more processors configured to:
detect a condition likely to cause instability in a pass-through signal path, wherein the condition likely to cause instability in the pass-through signal path comprises a condition likely to cause coupling between an output of the acoustic transducer and at least one of the one or more sensors; and
process the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path to generate a signal for the pass-through signal path;
wherein the acoustic transducer is driven by a drive signal that is based in part on the signal for the pass-through signal path.
33 . The device of claim 32 , wherein the one or more processors are configured to detect the condition likely to cause instability in the pass-through signal path by processing at least one of the input signal produced by the one or more sensors or another signal produced by one or more other sensors with a machine learning model to predict a probability of an existence of the condition likely to cause instability in the pass-through signal path.
34 . The device of claim 32 , wherein the one or more processors are configured to:
responsive to detecting the condition likely to cause instability in the pass-through signal path, train a machine learning model to predict a probability of an existence of the condition likely to cause instability in the pass-through signal path based on at least one of the input signal produced by the one or more sensors or another signal produced by one or more other sensors.
35 . The device of claim 32 , wherein the condition likely to cause instability in the pass-through signal path comprises a condition likely to cause coupling between at least a portion of the input signal passed through the pass-through signal path and the at least one of the one or more sensors.
36 . The device of claim 32 , wherein the one or more processors are configured to detect the condition likely to cause instability in the pass-through signal path by detecting, using one or more second sensors, that an object is within a predetermined distance from at least one of the one or more sensors or the one or more second sensors.
37 . The device of claim 32 , wherein the one or more processors are configured to process the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path by selecting a gain for the pass-through signal path based on the detected condition.
38 . The device of claim 32 , wherein the one or more processors are configured to process the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path by selecting one or more coefficients for a filter disposed in the pass-through signal path based on the detected condition.
39 . The device of claim 32 , wherein the one or more processors are configured to process the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path by disabling the pass-through signal path.
40 . A device, comprising:
one or more processors; and
memory storing instructions executable by the one or more processors to perform operations comprising:
receiving an input signal produced by one or more sensors;
detecting a condition likely to cause instability in a pass-through signal path, wherein the condition likely to cause instability in the pass-through signal path comprises a condition likely to cause coupling between an output of an acoustic transducer and at least one of the one or more sensors;
processing the input signal in accordance with the detected condition likely to cause instability in the pass-through signal path to generate a signal for the pass-through signal path; and
generating a drive signal for the acoustic transducer based in part on the signal for the pass-through signal path.