IP Library Granted Patent US 10,706,868
Granted Patent B2
US 10,706,868 · App. 15/697,176 · Granted Jul 7, 2020

Multi-mode noise cancellation for voice detection

Inventors: Sanjay Subir Jhawar (Menlo Park, CA); Christopher Iain Parkinson (Richland, WA); Kenneth Lustig (Mercer Island, WA)
Assignee: REALWEAR, INC.
G10L21/02G10L21/0208G10L25/84H04R1/1083H04R3/00H04R1/1008H04R2460/13H04S7/304
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Quick Facts
Patent No.
US 10,706,868
App. No.
15/697,176
Granted
Jul 7, 2020
Kind
B2
Abstract

Methods and systems provide dynamic selection of noise-cancelling algorithms, and dynamic activation and deactivation of microphones to provide multi-mode noise cancellation for a voice-detecting headset in situations where ambient noise prevents voice navigation from accurately interpreting voice commands. To do so, when an ambient noise is detected that exceeds a threshold, a particular noise-cancelling algorithm best-suited for the situation is selected, and one or more noise-detecting microphones is activated. The noise-detecting microphone(s) receiving the highest level of ambient noise can remain activated while the remaining noise-detecting microphones can be deactivated. A speech signal received by the speech microphone can then be optimized by cancelling the ambient noise signal received from the activated noise-detecting microphone(s) using the selected noise-cancelling algorithm. After the speech signal is optimized, it can be communicated to the voice-detecting headset for interpretation.

Claims (41)

1. A computer-implemented method of multi-modal noise cancellation for voice detection in a voice-detecting headset, the method comprising:

initializing a speech microphone of the voice-detecting headset, the voice-detecting headset having a plurality of noise-detecting microphones;

detecting an ambient noise in the speech microphone;

upon determining the ambient noise detected in the speech microphone exceeds a threshold, activating the plurality of noise-detecting microphones;

determining that one or more of the plurality of noise-detecting microphones is detecting higher energy levels of the ambient noise compared to the energy levels detected by remaining noise-detecting microphones of the plurality of noise-detecting microphones;

dynamically selecting a noise-cancelling algorithm from a plurality of different noise-cancelling algorithms based on at least one sound characteristic of the ambient noise detected by the one or more of the plurality of noise-detecting microphones; and

optimizing a speech signal received by the speech microphone by cancelling an ambient noise signal in the speech signal using the dynamically selected noise-cancelling algorithm, the ambient noise signal being received by the speech microphone and the one or more of the plurality of noise-detecting microphones detecting the higher energy levels of the ambient noise than the remaining noise-detecting microphones of the plurality of noise-detecting microphones.

2. The computer-implemented method of claim 1 , further comprising, after the speech signal is optimized, communicating the speech signal to the voice-detecting headset for interpretation.

3. The computer-implemented method of claim 1 , further comprising deactivating the remaining noise-detecting microphones.

4. The computer-implemented method of claim 1 , wherein at least one of the plurality of noise-detecting microphones is a stand-alone microphone that is located in proximity to the voice-detecting headset.

5. The computer-implemented method of claim 1 , wherein the speech microphone is a bone-conducting microphone.

6. The computer-implemented method of claim 1 , wherein the speech microphone is a cheek microphone.

7. The computer-implemented method of claim 1 , wherein the dynamically selected noise-cancelling algorithm is useable for filtering out voices of nearby speakers.

8. The computer-implemented method of claim 1 , wherein the dynamically selected noise-cancelling algorithm is useable for filtering out high-noise environments.

9. The computer-implemented method of claim 1 , wherein the voice-detecting headset comprises a head-mounted computing device having a display, and wherein the dynamically selected noise-cancelling algorithm is initiated by a processor of the head-mounted computing device.

10. The computer-implemented method of claim 1 , wherein the dynamically selected noise-cancelling algorithm is selected based on the detected ambient noise being above or below a threshold.

11. At least one non-transitory computer storage media, having instructions stored thereon that, when executed by at least one processor of a computing system, cause the computing system to:

initialize a speech microphone of a voice-detecting headset, the voice-detecting headset also having a plurality of noise-detecting microphones;

detect an ambient noise in a speech signal received by the speech microphone;

dynamically select a noise-cancelling algorithm from a plurality of different noise-cancelling algorithms based at least on a sensed energy level of the detected ambient noise, wherein the selected noise-cancelling algorithm comprises:

a first noise-cancelling algorithm useable for reducing a first type of ambient noise signal present in the speech signal, the first noise-cancelling algorithm selected based on the sensed energy level being below a threshold, or

a second noise-cancelling algorithm useable for reducing a second type of ambient noise signal present in the speech signal, wherein the second noise-cancelling algorithm is selected based on the sensed energy level being above the threshold;

optimize the speech signal received by the speech microphone by cancelling an ambient noise signal from the speech signal using the dynamically selected noise-cancelling algorithm, the ambient noise signal being received by the speech microphone and at least one dynamically selected noise-detecting microphone of the plurality of noise-detecting microphones; and

communicate the optimized speech signal to the voice-detecting headset for interpretation.

12. The at least one non-transitory computer storage media of claim 11 , wherein the dynamically selected noise-detecting microphone is determined based on one of the plurality of noise-detecting microphones detecting higher energy levels of the ambient noise compared to energy levels of the ambient noise detected by remaining noise-detecting microphones of the plurality of noise-detecting microphones.

13. The at least one non-transitory computer storage media of claim 12 , wherein the voice-detecting headset comprises a head-mounted computing device having a display, and wherein the dynamically selected noise-cancelling algorithm is initiated by the at least one processor which forms part of the head-mounted computing device.

14. The at least one non-transitory computer storage media of claim 12 , further comprising deactivating the remaining noise-detecting microphones.

15. The at least one non-transitory computer storage media of claim 11 , wherein the first noise-cancelling algorithm is useable for filtering out voices of nearby speakers, and wherein the second noise-cancelling algorithm is useable for filtering out high-noise environments.

16. A computerized system comprising:

at least one processor; and

at least one computer storage media storing computer-useable instructions thereon that, when executed by the at least one processor, causes the at least one processor to:

detect an ambient noise in a speech signal received by a voice-detecting headset comprising a speech microphone and a plurality of noise-detecting microphones;

dynamically select a noise-cancelling algorithm from a plurality of different noise-cancelling algorithms based on a detected ambient noise level, wherein the dynamically selected noise-cancelling algorithm comprises:

a first noise-cancelling algorithm useable for reducing a first type of ambient noise signal present in the speech signal, the first noise-cancelling algorithm selected based on the detected ambient noise level being below a threshold, or

a second noise-cancelling algorithm useable for reducing a second type of ambient noise signal present in the speech signal, the second noise-cancelling algorithm selected based on the detected ambient noise level being above the threshold;

determine that one or more of the plurality of noise-detecting microphones is detecting higher energy levels of the ambient noise compared to energy levels of the ambient noise detected by the remaining noise-detecting microphones; and

optimize the speech signal received by the speech microphone by cancelling an ambient noise signal from the speech signal using the dynamically selected noise-cancelling algorithm, the ambient noise signal received at least by the speech microphone and the one or more of the plurality of noise-detecting microphones.

17. The computerized system of claim 16 , wherein the first noise-cancelling algorithm is useable for filtering out voices of nearby speakers, and wherein the second noise-cancelling algorithm is useable for filtering out high-noise environments.

18. The computerized system of claim 16 , further comprising deactivating the remaining noise-detecting microphones.

19. The computerized system of claim 16 , wherein the voice-detecting headset comprises a head-mounted computing device having a display, and wherein the dynamically selected noise-cancelling algorithm is initiated by the at least one processor which forms part of the head-mounted computing device.

20. The computerized system of claim 16 , wherein the dynamically selected noise-cancelling algorithm is suited for filtering out the ambient noise signal received by the speech microphone and the one or more of the plurality of noise-detecting microphones.

Assignments (5)
SECURITY INTEREST Recorded Jun 6, 2024
From: REALWEAR, INC.
To: WESTERN ALLIANCE BANK
Reel/Frame 067646/0492 →
RELEASE OF SECURITY INTEREST Recorded Aug 21, 2023
From: RUNWAY GROWTH CREDIT FUND INC.
To: REALWEAR INC.
Reel/Frame 064654/0807 →
SECURITY INTEREST Recorded Aug 1, 2019
From: REALWEAR, INC.
To: RUNWAY GROWTH CREDIT FUND INC.
Reel/Frame 049933/0662 →
SECURITY INTEREST Recorded Feb 23, 2019
From: REALWEAR, INC.
To: RUNWAY GROWTH CREDIT FUND INC.
Reel/Frame 048418/0485 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 7, 2017
From: JHAWAR, SANJAY SUBIR; PARKINSON, CHRISTOPHER IAIN; LUSTIG, KENNETH
To: REALWEAR, INCORPORATED
Reel/Frame 043525/0534 →
Continuity (1)
Related Publication 20190074023A1 · Mar 7, 2019