Mobile platform based active noise cancellation (ANC)

Patent metadata

Field	Value
Publication number	US-10878796-B2
Application number	US-201916521069-A
Country	US
Kind code	B2
Filing date	Jul 24, 2019
Priority date	Oct 10, 2018
Publication date	Dec 29, 2020
Grant date	Dec 29, 2020

Abstract

A system and method for remote active noise correction at a remote device includes receiving, at the remote device, an ambient noise signal from a microphone. The remote device is disposed along a processing and transmission path between the microphone and a headphone. The processing and transmission path exhibit non-zero latency. The remote device further analyzes the ambient noise signal to generate an anti-noise signal, performs a first correction of the anti-noise signal for a headphone interface effect, performs a second correction of the anti-noise signal for the non-zero latency of the processing and transmission path between the microphone and the headphone. The remote device then transmits the corrected anti-noise signal to the headphone.

First claim

What is claimed is:

1. A method of remote active noise correction at a remote device, the method comprising:
receiving, at a processor of the remote device, an ambient noise signal from a microphone, wherein the remote device is disposed along a processing and transmission path between the microphone and a headphone, the processing and transmission path exhibiting non-zero latency;
analyzing, by the processor, the ambient noise signal to generate an anti-noise signal;
performing, by the processor, a first correction of the anti-noise signal for a headphone interface effect, the headphone interface effect arising between the headphone and a designated listening point;
performing, by the processor, a second correction of the anti-noise signal for the non-zero latency of the processing and transmission path between the microphone and the headphone; and
transmitting the corrected anti-noise signal to the headphone.

2. The method of claim 1 , further comprising:
performing a third correction of the anti-noise signal for a microphone location effect.

3. The method of claim 1 , further comprising:
generating a fast Fourier transform (FFT) of the ambient noise signal to obtain a representation of the ambient noise signal in a frequency domain,
wherein performing the second correction of the anti-noise signal is based on multiplying the FFT of the ambient noise signal by e −jωΔt such that
x ( n−Δt )↔ e −jωΔt *X (ω k )

wherein Δt represents the non-zero latency of the processing and transmission path between the microphone and the headphone,
wherein x is the ambient noise signal in a time domain, and
wherein X(ω k ) represents the FFT of x.

4. The method of claim 1 , further comprising:
generating a fast Fourier transform (FFT) of the ambient noise signal to obtain a representation of the ambient noise signal in a frequency domain; and
selecting a subset of noise peaks of the FFT above a threshold amplitude value,
wherein performing the second correction to the anti-noise signal is based on a cancellation of the selected subset of noise peaks of the FFT.

5. The method of claim 1 , further comprising:
generating a sample of the ambient noise signal; and
passing the sample of the ambient noise signal through an all-pass filter implementing a frequency dependent phase shift function to obtain an output,
wherein performing the second correction to the anti-noise signal is based on the output of the all-pass filter.

6. The method of claim 1 , further comprising:
generating a sample of the ambient noise signal; and
applying a machine learning algorithm to obtain a prediction of the ambient noise signal at a future time,
wherein performing the second correction to the anti-noise signal is based on the prediction of the ambient noise signal at the future time.

7. The method of claim 1 , further comprising:
determining a headphone profile for the headphone,
wherein performing the first correction of the anti-noise signal is based on the determined headphone profile, and
wherein the headphone profile comprises a prediction of the headphone interface effect for the headphone.

8. The method of claim 1 , further comprising:
determining a sound profile for the ambient noise signal,
wherein performing the second correction of the anti-noise signal is based on the determined sound profile,
wherein the sound profile comprises a prediction of one or more dominant frequency components of the ambient noise signal.

9. A remote device, comprising:
an audio interface connected to a microphone and a headphone;
a processor; and
a memory, containing instructions, which, when executed by the processor cause the remote device to:
receive, by the processor, an ambient noise signal from the microphone, wherein the remote device is disposed along a processing and transmission path between the microphone and the headphone, the processing and transmission path exhibiting non-zero latency,
analyze, by the processor, the ambient noise signal to generate an anti-noise signal,
perform, by the processor, a first correction of the anti-noise signal for a headphone interface effect, the headphone interface effect arising between the headphone and a designated listening point,
perform, by the processor, a second correction of the anti-noise signal for the non-zero latency of the processing and transmission path between the microphone and the headphone, and
transmit the corrected anti-noise signal to the headphone.

10. The remote device of claim 9 , wherein the memory contains instructions, which when executed by the processor, cause the remote device to:
perform a third correction of the anti-noise signal for a microphone location effect.

11. The remote device of claim 9 , wherein the memory contains instructions, which when executed by the processor, cause the remote device to:
generate a fast Fourier transform (FFT) of the ambient noise signal to obtain a representation of the ambient noise signal in a frequency domain, and
perform the second correction of the anti-noise signal based on multiplying the FFT of the ambient noise signal by e −jωΔt such that
x ( n−Δt )↔ e −jωΔt *X (ω k )

wherein Δt represents the non-zero latency of the processing and transmission path between the microphone and the headphone,
wherein x is the ambient noise signal in a time domain, and
wherein X(ω k ) represents the FFT of x.

12. The remote device of claim 9 , wherein the memory contains instructions, which, when executed by the processor, cause the remote device to:
generate a fast Fourier transform (FFT) of the ambient noise signal to obtain a representation of the ambient noise signal in a frequency domain,
select a subset of noise peaks of the FFT above a threshold amplitude value, and
perform the second correction to the anti-noise signal based on a cancellation of the selected subset of noise peaks of the FFT.

13. The remote device of claim 9 , wherein the memory contains instructions, which, when executed by the processor, cause the remote device to:
generate a sample of the ambient noise signal,
pass the sample of the ambient noise signal through an all-pass filter implementing a frequency dependent phase shift function to obtain an output, and
perform the second correction to the anti-noise signal based on the output of the all-pass filter.

14. The remote device of claim 9 , wherein the memory contains instructions, which when executed by the processor, cause the remote device to:
generate a sample of the ambient noise signal,
apply a machine learning algorithm to obtain a prediction of the ambient noise signal at a future time, and
perform the second correction to the anti-noise signal based on the prediction of the ambient noise signal at the future time.

15. The remote device of claim 9 , wherein the memory contains instructions, which when executed by the processor, cause the remote device to:
determine a headphone profile for the headphone, and
perform the first correction of the anti-noise signal based on the determined headphone profile,
wherein the headphone profile comprises a prediction of the headphone interface effect for the headphone.

16. The remote device of claim 9 , wherein the memory contains instructions, which, when executed by the processor, cause the remote device to:
determine a sound profile for the ambient noise signal, and
perform the second correction of the anti-noise signal based on the determined sound profile,
wherein the sound profile comprises a prediction of one or more dominant frequency components of th

Assignees

• Samsung Electronics Co Ltd

Inventors

• Zhao Ye
• Wortham Cody
• Young James
• Sadi Sajid
• Kim Paul
• Moon Bo Hyun

Classifications

• G10K11/17873 Primary

  using a reference signal without an error signal, e.g. pure feedforward · CPC title

• G10K2210/1081

  Earphones, e.g. for telephones, ear protectors or headsets · CPC title

• G10K11/17853

  of the filter · CPC title

• G10K2210/3028

  Filtering, e.g. Kalman filters or special analogue or digital filters · CPC title

• G10K11/17823 Primary

  Reference signals, e.g. ambient acoustic environment · CPC title