IP Library Granted Patent US 11,714,600
Granted Patent B2
US 11,714,600 · App. 17/662,302 · Granted Aug 1, 2023

Noise classification for event detection

Inventors: Nick D'Amato (Santa Barbara, CA); Kurt Thomas Soto (Ventura, CA); Connor Kristopher Smith (New Hudson, MI)
Assignee: Sonos, Inc.
G06F3/167G06F3/162G06F3/165G10L15/22H04L12/2809H04R3/12H04R2227/005
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Quick Facts
Patent No.
US 11,714,600
App. No.
17/662,302
Granted
Aug 1, 2023
Kind
B2
Abstract

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.

Claims (62)

1. A network microphone device (NMD), comprising:

one or more processors;

one or more microphones; and

data storage storing instructions executable by the one or more processors to cause the NMD to perform operations comprising:

detecting sound via one or more microphones, wherein the detected sound incudes a voice utterance;

capturing first sound data via the NMD based on the detected sound;

analyzing, via the NMD, the first sound data to detect a wake word;

based on the analyzed first sound data, detecting the wake word;

after detecting the wake word, transmitting at least the voice utterance to one or more remote computing devices associated with a voice assistant service;

detecting additional sound via the one or more microphones;

capturing second sound data via the NMD based on the detected additional sound;

analyzing, via the NMD, the second sound data to detect the wake word, wherein the wake word is not detected based on the analyzed second sound data;

capturing metadata associated with the detected additional sound via the NMD;

processing the metadata to classify one or more noises in the detected additional sound; and

causing the NMD to perform an action based on the classification of the respective one or more noises.

2. The NMD of claim 1 , wherein capturing the first sound data via the NMD comprises capturing the first sound data in a first portion of memory of the NMD.

3. The NMD of claim 2 , wherein capturing the second sound data via the NMD comprises capturing the second sound data in the first portion of memory of the NMD.

4. The NMD of claim 2 , wherein capturing metadata associated with the detected additional sound via the NMD comprises capturing metadata associated with the detected sound via a second portion of memory of the NMD.

5. The NMD of claim 1 , wherein:

the second sound data comprises recorded audio; and

the metadata comprises spectral information that is temporally disassociated from the recorded audio.

6. The NMD of claim 1 , wherein processing the metadata comprises transmitting the metadata to one or more other remote servers for analyzing the metadata.

7. The NMD of claim 1 , wherein processing the metadata comprises locally analyzing the metadata and classifying the one or more noises via the NMD.

8. A method comprising:

detecting sound via one or more microphones of a network microphone device (NMD), wherein the detected sound incudes a voice utterance;

capturing first sound data via the NMD based on the detected sound;

analyzing, via the NMD, the first sound data to detect a wake word;

based on the analyzed first sound data, detecting the wake word;

after detecting the wake word, transmitting at least the voice utterance to one or more remote computing devices associated with a voice assistant service;

detecting additional sound via the one or more microphones;

capturing second sound data via the NMD based on the detected additional sound;

analyzing, via the NMD, the second sound data to detect the wake word, wherein the wake word is not detected based on the analyzed second sound data;

capturing metadata associated with the detected additional sound via the NMD;

processing the metadata to classify one or more noises in the detected additional sound; and

causing the NMD to perform an action based on the classification of the respective one or more noises.

9. The method of claim 8 , wherein capturing the first sound data via the NMD comprises capturing the first sound data in a first portion of memory of the NMD.

10. The method of claim 9 , wherein capturing the second sound data via the NMD comprises capturing the second sound data in the first portion of memory of the NMD.

11. The method of claim 9 , wherein capturing metadata associated with the detected additional sound via the NMD comprises capturing metadata associated with the detected sound via a second portion of memory of the NMD.

12. The method of claim 8 , wherein:

the second sound data comprises recorded audio; and

the metadata comprises spectral information that is temporally disassociated from the recorded audio.

13. The method of claim 8 , wherein processing the metadata comprises transmitting the metadata to one or more other remote servers for analyzing the metadata.

14. The method of claim 8 , wherein processing the metadata comprises locally analyzing the metadata and classifying the one or more noises via the NMD.

15. One or more tangible, non-transitory, computer-readable media storing instructions executable by one or more processors to cause a network microphone device (NMD) to perform operations comprising:

detecting sound via one or more microphones, wherein the detected sound incudes a voice utterance;

capturing first sound data via the NMD based on the detected sound;

analyzing, via the NMD, the first sound data to detect a wake word;

based on the analyzed first sound data, detecting the wake word;

after detecting the wake word, transmitting at least the voice utterance to one or more remote computing devices associated with a voice assistant service;

detecting additional sound via the one or more microphones;

capturing second sound data via the NMD based on the detected additional sound;

analyzing, via the NMD, the second sound data to detect the wake word, wherein the wake word is not detected based on the analyzed second sound data;

capturing metadata associated with the detected additional sound via the NMD;

processing the metadata to classify one or more noises in the detected additional sound; and

causing the NMD to perform an action based on the classification of the respective one or more noises.

16. The one or more computer-readable media of claim 15 , wherein capturing the first sound data via the NMD comprises capturing the first sound data in a first portion of memory of the NMD.

17. The one or more computer-readable media of claim 16 , wherein capturing the second sound data via the NMD comprises capturing the second sound data in the first portion of memory of the NMD.

18. The one or more computer-readable media of claim 16 , wherein capturing metadata associated with the detected additional sound via the NMD comprises capturing metadata associated with the detected sound via a second portion of memory of the NMD.

19. The one or more computer-readable media of claim 15 , wherein:

the second sound data comprises recorded audio; and

the metadata comprises spectral information that is temporally disassociated from the recorded audio.

20. The one or more computer-readable media of claim 15 , wherein processing the metadata comprises transmitting the metadata to one or more other remote servers for analyzing the metadata.

Assignments (2)
SECURITY INTEREST Recorded Jan 30, 2026
From: SONOS, INC.
To: JPMORGAN CHASE BANK, N.A., AS ADMINISTRATIVE AGENT
Reel/Frame 074533/0615 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded May 6, 2022
From: D'AMATO, NICK; SOTO, KURT THOMAS; SMITH, CONNOR KRISTOPHER
To: SONOS, INC.
Reel/Frame 059842/0462 →
Continuity (3)
Continuation 17247736 · Dec 21, 2020
Continuation 16528016 · Jul 31, 2019
Related Publication 20220365747A1 · Nov 17, 2022
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