Device impairment detection
First Claim
1. A non-transitory computer-readable medium having stored therein instructions executable by one or more processors to cause a control device to perform operations comprising:
- receiving data indicating a detected response of one or more playback devices captured by a microphone;
determining a calibration profile of the one or more playback devices based on the data, wherein the calibration profile comprises an output frequency response of the one or more playback devices;
determining an input vector by projecting a response vector that represents the detected response of the one or more playback devices onto a principle component matrix representing variance caused by one or more calibration impairments;
providing the determined input vector to a neural network that includes an output layer comprising neurons that correspond to respective calibration impairments;
detecting that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that one or more particular calibration impairments are affecting the microphone; and
adjusting the output frequency response of the one or more playback devices to offset the one or more particular calibration impairments.
6 Assignments
0 Petitions
Accused Products
Abstract
Examples described herein involve detecting known impairments or other known conditions using a neural network. An example implementation involves receiving data indicating a response of a playback device as captured by a microphone. The implementation also involves determining an input vector by projecting a response vector that represents the response of the playback device onto a principle component matrix representing variance caused by one or more known impairments. The implementation further involves providing the determined input vector to a neural network that includes an output layer comprising neurons that correspond to respective known impairments. The implementation involves detecting that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that a particular known impairment is affecting the microphone and/or the playback device and adjusting operation of the playback device and/or the microphone to offset the particular known impairment.
45 Citations
20 Claims
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1. A non-transitory computer-readable medium having stored therein instructions executable by one or more processors to cause a control device to perform operations comprising:
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receiving data indicating a detected response of one or more playback devices captured by a microphone; determining a calibration profile of the one or more playback devices based on the data, wherein the calibration profile comprises an output frequency response of the one or more playback devices; determining an input vector by projecting a response vector that represents the detected response of the one or more playback devices onto a principle component matrix representing variance caused by one or more calibration impairments; providing the determined input vector to a neural network that includes an output layer comprising neurons that correspond to respective calibration impairments; detecting that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that one or more particular calibration impairments are affecting the microphone; and adjusting the output frequency response of the one or more playback devices to offset the one or more particular calibration impairments. - View Dependent Claims (2, 3, 4, 5, 6, 7, 8, 9, 10, 11)
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12. A playback device comprising:
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one or more processors; a tangible data storage having stored therein instructions executable by the one or more processors to cause the playback device to perform operations comprising; receiving data indicating a detected response of the playback device in a given environment which was captured with a recording device; determining a calibration profile of the playback device based on the data, wherein the calibration profile comprises an output frequency response of the playback device; determining an input vector by projecting a response vector that represents the detected response of the playback device onto a principle component matrix representing variance caused by one or more conditions; providing the determined input vector to a neural network that includes an output layer comprising neurons that correspond to respective conditions; detecting that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that one or more particular conditions are affecting the recording device; and adjusting the output frequency response of the playback device to offset the one or more particular conditions. - View Dependent Claims (13, 14, 15)
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16. A method comprising:
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receiving, by a computing device, data indicating a detected response of one or more playback devices captured by a microphone; determining, by the computing device, a calibration profile of the one or more playback devices based on the data, wherein the calibration profile comprises an output frequency response of the one or more playback devices; determining, by the computing device, an input vector by projecting a response vector that represents the detected response of the one or more playback devices onto a principle component matrix representing variance caused by one or more calibration impairments; providing, by the computing device, the determined input vector to a neural network that includes an output layer comprising neurons that correspond to respective calibration impairments; detecting, by the computing device, that the input vector caused one or more neurons of the neural network to fire such that the neural network indicates that one or more particular calibration impairments are affecting the microphone; and adjusting, by the computing device, the output frequency response of the one or more playback devices to offset the one or more particular calibration impairments. - View Dependent Claims (17, 18, 19, 20)
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Specification