Abstract: Systems and methods for maintaining voice assistant persistence across multiple network microphone devices are described. In one example, first and second NMDs each identify a wake word based on detected sound, and are each transitioned from an inactive state to an active state in which the NMD captures and transmits sound data over a network interface. The first NMD is selected over the second NMD to output a first response, and both NMDs remain in the active state to further capture and transmit sound data. After further capturing and transmitting of sound data, the second NMD is selected over the first NMD to output a second response. After a predetermined time, one or both of the NMDs are transitioned back to the inactive state. The selection of one NMD over another for outputting a response can be based at least in part on user location information.

Abstract: Systems and methods for optimizing voice detection via a network microphone device (NMD) based on a selected voice-assistant service (VAS) are disclosed herein. In one example, the NMD detects sound via individual microphones and selects a first VAS to communicate with the NMD. The NMD produces a first sound-data stream based on the detected sound using a spatial processor in a first configuration. Once the NMD determines that a second VAS is to be selected over the first VAS, the spatial processor assumes a second configuration for producing a second sound-data stream based on the detected sound. The second sound-data stream is then transmitted to one or more remote computing devices associated with the second VAS.

Abstract: Systems and methods for distributed voice processing are disclosed herein. In one example, the method includes detecting sound via a microphone array of a first playback device and analyzing, via a first wake-word engine of the first playback device, the detected sound. The first playback device may transmit data associated with the detected sound to a second playback device over a local area network. A second wake-word engine of the second playback device may analyze the transmitted data associated with the detected sound. The method may further include identifying that the detected sound contains either a first wake word or a second wake word based on the analysis via the first and second wake-word engines, respectively. Based on the identification, sound data corresponding to the detected sound may be transmitted over a wide area network to a remote computing device associated with a particular voice assistant service.

Abstract: Systems and methods for distributed voice processing are disclosed herein. In one example, the method includes detecting sound via a microphone array of a first playback device and analyzing, via a first wake-word engine of the first playback device, the detected sound. The first playback device may transmit data associated with the detected sound to a second playback device over a local area network. A second wake-word engine of the second playback device may analyze the transmitted data associated with the detected sound. The method may further include identifying that the detected sound contains either a first wake word or a second wake word based on the analysis via the first and second wake-word engines, respectively. Based on the identification, sound data corresponding to the detected sound may be transmitted over a wide area network to a remote computing device associated with a particular voice assistant service.

Abstract: In one aspect, a playback device is provided that is configured to identify a trigger event indicating a request to associate the playback device with another playback device. Based on identifying the trigger event, the playback device is configured to create a first sound code based on a first sound specimen detected by the playback device. After identifying the trigger event, the playback device is configured to receive from the other playback device a sound object and based on receiving the sound object, identify a second sound code. The playback device is also configured to, based on the first sound code and the second sound code, determine that it and the other playback device have a spatial relationship. Based on that determination, the playback device is configured to cause it and the other playback device to be associated in accordance with the indicated request.

Abstract: Systems and methods for optimizing voice detection via a network microphone device (NMD) based on a selected voice-assistant service (VAS) are disclosed herein. In one example, the NMD detects sound via individual microphones and selects a first VAS to communicate with the NMD. The NMD produces a first sound-data stream based on the detected sound using a spatial processor in a first configuration. Once the NMD determines that a second VAS is to be selected over the first VAS, the spatial processor assumes a second configuration for producing a second sound-data stream based on the detected sound. The second sound-data stream is then transmitted to one or more remote computing devices associated with the second VAS.

Abstract: Systems and methods for optimizing voice detection via a network microphone device are disclosed herein. In one example, individual microphones of a network microphone device detect sound. The sound data is captured in a first buffer and analyzed to detect a trigger event. Metadata associated with the sound data is captured in a second buffer and provided to at least one network device to determine at least one characteristic of the detected sound based on the metadata. The network device provides a response that includes an instruction, based on the determined characteristic, to modify at least one performance parameter of the NMD. The NMD then modifies the at least one performance parameter based on the instruction.

Abstract: Systems and methods for optimizing voice detection via a network microphone device (NMD) based on a selected voice-assistant service (VAS) are disclosed herein. In one example, the NMD detects sound via individual microphones and selects a first VAS to communicate with the NMD. The NMD produces a first sound-data stream based on the detected sound using a spatial processor in a first configuration. Once the NMD determines that a second VAS is to be selected over the first VAS, the spatial processor assumes a second configuration for producing a second sound-data stream based on the detected sound. The second sound-data stream is then transmitted to one or more remote computing devices associated with the second VAS.

Abstract: In one aspect, a playback deice is configured to identify in an audio stream, via a second wake-word engine, a false wake word for a first wake-word engine that is configured to receive as input sound data based on sound detected by a microphone. The first and second wake-word engines are configured according to different sensitivity levels for false positives of a particular wake word. Based on identifying the false wake word, the playback device is configured to (i) deactivate the first wake-word engine and (ii) cause at least one network microphone device to deactivate a wake-word engine for a particular amount of time. While the first wake-word engine is deactivated, the playback device is configured to cause at least one speaker to output audio based on the audio stream. After a predetermined amount of time has elapsed, the playback device is configured to reactivate the first wake-word engine.

Abstract: In one aspect, a playback device is provided that is configured to identify a trigger event indicating a request to associate the playback device with another playback device. Based on identifying the trigger event, the playback device is configured to create a first sound code based on a first sound specimen detected by the playback device. After identifying the trigger event, the playback device is configured to receive from the other playback device a sound object and based on receiving the sound object, identify a second sound code. The playback device is also configured to, based on the first sound code and the second sound code, determine that it and the other playback device have a spatial relationship. Based on that determination, the playback device is configured to cause it and the other playback device to be associated in accordance with the indicated request.

Abstract: In one aspect, a playback device is provided that is configured to identify a trigger event indicating a request to associate the playback device with another playback device. Based on identifying the trigger event, the playback device is configured to create a first sound code based on a first sound specimen detected by the playback device. After identifying the trigger event, the playback device is configured to receive from the other playback device a sound object and based on receiving the sound object, identify a second sound code. The playback device is also configured to, based on the first sound code and the second sound code, determine that it and the other playback device have a spatial relationship. Based on that determination, the playback device is configured to cause it and the other playback device to be associated in accordance with the indicated request.

Abstract: Systems and methods for optimizing voice detection via a network microphone device (NMD) based on a selected voice-assistant service (VAS) are disclosed herein. In one example, the NMD detects sound via individual microphones and selects a first VAS to communicate with the NMD. The NMD produces a first sound-data stream based on the detected sound using a spatial processor in a first configuration. Once the NMD determines that a second VAS is to be selected over the first VAS, the spatial processor assumes a second configuration for producing a second sound-data stream based on the detected sound. The second sound-data stream is then transmitted to one or more remote computing devices associated with the second VAS.

Abstract: Systems and methods for determining and adapting to changes in microphone performance of playback devices are disclosed herein. In one example, an audio input is received at an array of individual microphones of a network microphone device. Output microphone signals are generated from each of the individual microphones based on the audio input. The output microphone signals are analyzed to detect a trigger event. After detecting the trigger event, the output microphone signals are compared to detect aberrant behavior of one or more of the microphones. Optionally, corrective actions can be taken or suggested based on the detection of aberrant behavior of one or more microphones.