Sonos, Inc.

Nick D'Amato

Connor Kristopher Smith

Kurt Thomas Soto

Timothy W Sheen

Dayn Wilberding

Benjamin M Rappoport

Hilmar Lehnert

Klaus Hartung

Daniele Giacobello

Andrea Testa

Nash Reilly

Joachim Fainberg

Systems and methods disclosed herein include, determining a proximity of the first networked device to a second networked device, determining whether there is a wired network connection existing between the first networked device and the second networked device, and in response to determining the proximity and the existence of a wired network connection, reconfiguring one or more operational parameters of one or both of the first networked device and the second networked device.

Proximal playback devices

In one aspect, a playback device includes a command-keyword engine having a local natural language unit (NLU). The playback device detects, via the command-keyword engine, a first command keyword in voice input of sound detected by one or more microphones of the playback device. The playback device determines whether the sound input data includes a keyword from a first predetermined library of keywords via a local natural language unit (NLU). The playback device transmits the input sound data to a second playback device over a local area network, the second playback device employing a second local NLU with a second predetermined library of keywords. The playback device receives a response from the second playback device and performs an action based on an intent determined by at least one of the first NLU or the second NLU according to the keywords in the voice input.

Locally distributed keyword detection

In one aspect, a network microphone device includes a plurality of microphones and is configured to detect sound via the one or more microphones. The network microphone device may capture sound data based on the detected sound in a first buffer, and capture metadata associated with the detected sound in a second buffer. The network microphone device may classify one or more noises in the detected sound and cause the network microphone device to perform an action based on the classification of the respective one or more noises.

Noise classification for event detection

Systems, methods, and devices with reduced power consumption in network microphone devices. In one embodiment, a network microphone device is configured to perform a method that includes (i) capturing audio content; (ii) using a first algorithm to perform a keyword detection process for determining whether the audio content includes a keyword; (iii) responsive to determining that the audio content includes the keyword, using a second, more computationally intensive algorithm to perform a wake-word detection process for determining whether the audio content includes a wake word; and (iv) responsive to performing the wake-word detection process, (a) causing a voice service corresponding to the wake word to process the audio content if the wake-word detection process confirms that the audio content includes the wake word or (b) ceasing performance of the wake-word detection process if the wake-word detection process disconfirms that the audio content includes the wake word.

Multiple stage network microphone device with reduced power consumption and processing load

In one aspect, a playback device includes at least one microphone configured to detect a voice input and generate sound input data. The playback device detects a first command keyword in the detected sound and, in response, makes a first determination, via a first local natural language unit (NLU), whether the input sound data includes at least one keyword within a first predetermined library of keywords. The playback device receives an indication of a second determination made by a second NLU that the input sound data includes at least one keyword from a second predetermined library of keywords. The playback device compares the results of the first determination and the second determination and, based on the comparison, foregoes further processing of the input sound data.

Systems and methods for authenticating a passive speaker include (i) activating, by a playback device configured to drive the passive speaker, a passive speaker identification circuit of the passive speaker by providing an identification signal to an input terminal of the passive speaker, wherein the passive speaker is a particular type of passive speaker having particular characteristics; (ii) while the passive speaker identification circuit is active, measuring, by the playback device, an electrical current of the identification signal; (iii) determining, based on the measured electrical current of the identification signal, an impedance modulation of the passive speaker; (iv) determining, by the playback device, the particular type of the passive speaker based on the impedance modulation of the passive speaker; and (v) applying, by the playback device, a calibration to the playback device based on the determined particular type of the passive speaker.

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Santa Barbara, CA, United States of America

Nick D'Amato