Abstract: Examples described herein involve detecting known impairments or other known conditions using a neural network. An example implementation receives a response matrix that represents, in respective dimensions, responses of a given playback device under respective iterations of a sound captured by a recording device, the iterations including first iterations with respective impairments to the recording device and second iterations without the respective impairments to the recording device. The implementation determines principle components representing the axes of greatest variance in the response matrix, a principle-component matrix that represents a given set of the principle components, and a teaching matrix by projecting the principle-component onto the response matrix.

Abstract: A computing device may maintain a database of representative spectral characteristics. The computing device may also receive particular spectral data associated with a particular playback environment corresponding to the particular playback device. Based on the particular spectral data, the computing device may identify one of the representative spectral characteristics from the database that substantially matches the particular spectral data, and then identify, in the database, an audio processing algorithm based on a) the identified representative spectral characteristic and b) at least one characteristic of the particular playback device. The computing device may then transmit, to the particular playback device, data indicating the identified audio processing algorithm.

Abstract: A computing device may transmit playback device configuration information to a given playback device. The computing device may then receive calibration data corresponding to each playback device of a plurality of playback devices, and receive playback device characteristic data indicating at least one playback device characteristic for each playback device of the plurality of playback devices. Based on at least the received calibration data and the received playback device characteristic data, the computing device may determine updated playback device configuration information and transmit data indicating the updated playback device configuration information to the given playback device.

Abstract: An audio playback device comprises a microphone, a speaker, and a processor. The processor is arranged to output by the speaker first audio content and receive by the microphone an indication of the first audio content. A first acoustic response of a room in which the audio playback device is located is determined based on the received indication of first audio content. A mapping is applied to the first acoustic response to determine a second acoustic response. The second acoustic response is indicative of an approximated acoustic response of the room at a spatial location different from a spatial location of the microphone. The second audio content output by the speaker is adjusted based on the second response.

Abstract: Example techniques may involve calibration with multiple recording devices. An implementation may include detecting, via a microphone, one or more calibration sounds as emitted by one or more playback devices of one or more zones during a calibration sequence. The implementation may further include determining a first response, the first response representing a response of a given environment to the one or more calibration sounds as detected by the first recording device and receiving data indicating a second response, the second response representing a response of the given environment to the one or more calibration sounds as detected by a second recording device. The implementation may also include determining a calibration for the one or more playback devices based on the first response and the second response and sending, to the one or more zones, an instruction that applies the calibration to playback by the one or more playback devices.

Abstract: A computing device may transmit playback device configuration information to a given playback device. The computing device may then receive calibration data corresponding to each playback device of a plurality of playback devices, and receive playback device characteristic data indicating at least one playback device characteristic for each playback device of the plurality of playback devices. Based on at least the received calibration data and the received playback device characteristic data, the computing device may determine updated playback device configuration information and transmit data indicating the updated playback device configuration information to the given playback device.

Abstract: A computing device may maintain a database of representative spectral characteristics. The computing device may also receive particular spectral data associated with a particular playback environment corresponding to the particular playback device. Based on the particular spectral data, the computing device may identify one of the representative spectral characteristics from the database that substantially matches the particular spectral data, and then identify, in the database, an audio processing algorithm based on a) the identified representative spectral characteristic and b) at least one characteristic of the particular playback device. The computing device may then transmit, to the particular playback device, data indicating the identified audio processing algorithm.

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.

Abstract: An audio playback device comprises a microphone, a speaker, and a processor. The processor is arranged to output by the speaker first audio content and receive by the microphone an indication of the first audio content. A first acoustic response of a room in which the audio playback device is located is determined based on the received indication of first audio content. A mapping is applied to the first acoustic response to determine a second acoustic response. The second acoustic response is indicative of an approximated acoustic response of the room at a spatial location different from a spatial location of the microphone. The second audio content output by the speaker is adjusted based on the second response.

Abstract: Example techniques may involve calibration with multiple recording devices. An implementation may include detecting, via a microphone, one or more calibration sounds as emitted by one or more playback devices of one or more zones during a calibration sequence. The implementation may further include determining a first response, the first response representing a response of a given environment to the one or more calibration sounds as detected by the first recording device and receiving data indicating a second response, the second response representing a response of the given environment to the one or more calibration sounds as detected by a second recording device. The implementation may also include determining a calibration for the one or more playback devices based on the first response and the second response and sending, to the one or more zones, an instruction that applies the calibration to playback by the one or more playback devices.

Abstract: An example method may involve a device determining a first loudness representation for a playback device based on a first equalization setting applied to a representation of average music. The device may also determine a second loudness representation for the playback device, based on a second equalization setting applied to the representation of average music. The device may also determine a loudness adjustment factor based on the first and second loudness representations, and then causing the playback device to play back media based on the second equalization setting and the determined loudness adjustment factor.

Abstract: Example techniques may involve multiple calibrations for one or more playback devices. An example implementation may involve detecting, via a microphone, calibration sounds as emitted by one or more playback devices during a calibration sequence, perhaps by recording first samples while the microphone is in motion through a given environment and recording second samples while the microphone is stationary at one or more particular locations. The implementation may also include determining a first calibration for the one or more playback devices based on at least the first samples of the calibrations sounds and determining a second calibration for the one or more playback devices based on at least the second samples of the calibrations sounds. The implementation may further include applying at least one of (a) the first calibration or (b) the second calibration to playback by the one or more playback devices.

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.

Abstract: An example method may involve a device determining a first loudness representation for a playback device based on a first equalization setting applied to a representation of average music. The device may also determine a second loudness representation for the playback device, based on a second equalization setting applied to the representation of average music. The device may also determine a loudness adjustment factor based on the first and second loudness representations, and then causing the playback device to play back media based on the second equalization setting and the determined loudness adjustment factor.

Abstract: An audio system for a vehicle has at least one source of audio signals. A respective directional loudspeaker array is mounted at each seat position and coupled to the at least one source. The at least one source includes a microphone that detects speech from an occupant of the first seat position. Processing circuitry receives signals from the microphone that correspond to the detect speech and drives each second respective loudspeaker array at the other seat positions to radiate acoustic energy corresponding to the detected speech.

Abstract: An example method may involve a device determining a first loudness representation for a playback device based on a first equalization setting applied to a representation of average music. The device may also determine a second loudness representation for the playback device, based on a second equalization setting applied to the representation of average music. The device may also determine a loudness adjustment factor based on the first and second loudness representations, and then causing the playback device to play back media based on the second equalization setting and the determined loudness adjustment factor.

Abstract: An audio system for a vehicle has at least one source of audio signals. A respective directional loudspeaker array is mounted at each seat position and coupled to the at least one source. The at least one source includes a microphone that detects speech from an occupant of the first seat position. Processing circuitry receives signals from the microphone that correspond to the detect speech and drives each second respective loudspeaker array at the other seat positions to radiate acoustic energy corresponding to the detected speech.

Abstract: An example method may involve a device determining a first loudness representation for a playback device based on a first equalization setting applied to a representation of average music. The device may also determine a second loudness representation for the playback device, based on a second equalization setting applied to the representation of average music. The device may also determine a loudness adjustment factor based on the first and second loudness representations, and then causing the playback device to play back media based on the second equalization setting and the determined loudness adjustment factor.

Abstract: A method for automatically switching an audio source includes the steps of receiving an audio signal from a video display device, and receiving a digital audio signal from one of a plurality of audio/video source devices which each can supply audio and video information to the video display device. The digital audio signal is compared with the audio signal from the video display device. The digital audio signal is output to a supplemental audio system of the video display device when the comparing step indicates that the digital audio signal and the audio signal from the video display device contain substantially similar audio programs.

Abstract: An audio conference system has a plurality of specially designed microphone housings into each of which a directional microphone is positioned. Each microphone housing is positioned entirely within the body of the audio conferencing system, the microphone housings are strategically positioned at each one of four corners of the audio conference system body in order to provide maximum exposure of a microphone to its operating environment, and the interior structure of the microphone housing is designing to reflect unwanted energy harmlessly away from the microphone. Each directional microphone is positioned in the microphone housing such that the most sensitive node in its polar response pattern is oriented normal (at right angles) to a line radiating outward from the center of the system.