IP Library Granted Patent US 11,218,125
Granted Patent B2
US 11,218,125 · App. 16/661,973 · Granted Jan 4, 2022

Methods and apparatus to adjust audio playback settings based on analysis of audio characteristics

Inventors: Robert Coover (Orinda, CA); Cameron Aubrey Summers (Oakland, CA); Todd Hodges (Oakland, CA); Joseph Renner (Oakland, CA); Markus Cremer (Orinda, CA); Matthew McCallum (San Francisco, CA)
Assignee: GRACENOTE, INC
H03G5/165G06F3/165G06N3/04G06N3/08G10L25/30G10L25/51H04N9/87H04N21/439H04N21/4524H04R3/04H03F3/181H04R2430/01H04R2499/13
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Quick Facts
Patent No.
US 11,218,125
App. No.
16/661,973
Granted
Jan 4, 2022
Kind
B2
Abstract

Methods, apparatus, systems and articles of manufacture are disclosed to adjust audio playback settings based on analysis of audio characteristics. Example apparatus disclosed herein include an equalization (EQ) model query generator to generate a query to a neural network, the query including a representation of a sample of an audio signal; an EQ filter settings analyzer to: access a plurality of audio playback settings determined by the neural network based on the query; and determine a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; and an EQ adjustment implementer to apply the filter coefficient to the audio signal in a first duration.

Claims (33)

1. An apparatus comprising:

an equalization (EQ) model query generator to generate a query to a neural network, the query including a representation of a sample of an audio signal, the neural network trained to mitigate different preferences associated with respective audio playback settings determined by at least two audio engineers that tailored the respective audio playback settings for a library of reference audio signals used to train the neural network;

an EQ filter settings analyzer to:

access a plurality of audio playback settings determined by the neural network based on the query; and

determine a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; and

an EQ adjustment implementor to apply the filter coefficient to the audio signal in a first duration.

2. The apparatus of claim 1 , wherein the representation of the sample of the audio signal corresponds to a constant-Q transform representation of the sample of the audio signal.

3. The apparatus of claim 1 , wherein the plurality of audio playback settings include filter settings associated with one or more filters, wherein the filter settings include one or more respective gain values, respective frequency values, or respective quality factor values associated with the sample of the audio signal.

4. The apparatus of claim 1 , wherein the EQ filter settings analyzer is to determine the filter coefficient to apply to the audio signal based on a type of a filter associated with the filter coefficient to be applied to the audio signal.

5. The apparatus of claim 1 , wherein the EQ adjustment implementor is to apply a smoothing filter to the audio signal to reduce sharp transitions in average gain values of the audio signal between the first duration and a second duration.

6. The apparatus of claim 1 , further including a signal transformer to transform the audio signal to a frequency representation of the sample of the audio signal.

7. The apparatus of claim 1 , wherein the EQ adjustment implementor is to adjust at least one of an amplitude characteristic, a frequency characteristic, or a phase characteristic of the audio signal based on the filter coefficient.

8. A non-transitory computer readable storage medium comprising instructions which, when executed, cause one or more processors to at least:

generate a query to a neural network, the query including a representation of a sample of an audio signal, the neural network trained to mitigate different preferences associated with respective audio playback settings determined by at least two audio engineers that tailored the respective audio playback settings for a library of reference audio signals used to train the neural network;

access a plurality of audio playback settings determined by the neural network based on the query;

determine a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; and

apply the filter coefficient to the audio signal in a first duration.

9. The non-transitory computer readable storage medium of claim 8 , wherein the representation of the sample of the audio signal corresponds to a constant-Q transform representation of the sample of the audio signal.

10. The non-transitory computer readable storage medium of claim 8 , wherein the plurality of audio playback settings include filter settings associated with one or more filters, wherein the filter settings include one or more respective gain values, respective frequency values, or respective quality factor values associated with the sample of the audio signal.

11. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the one or more processors to determine the filter coefficient to apply to the audio signal based on a type of a filter associated with the filter coefficient to be applied to the audio signal.

12. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the one or more processors to apply a smoothing filter to the audio signal to reduce sharp transitions in average gain values of the audio signal between the first duration and a second duration.

13. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the one or more processors to transform the audio signal to a frequency representation of the sample of the audio signal.

14. The non-transitory computer readable storage medium of claim 8 , wherein the instructions, when executed, cause the one or more processors to adjust at least one of an amplitude characteristic, a frequency characteristic, or a phase characteristic of the audio signal based on the filter coefficient.

15. A method comprising:

generating a query to a neural network, the query including a representation of a sample of an audio signal, the neural network trained to mitigate different preferences associated with respective audio playback settings determined by at least two audio engineers that tailored the respective audio playback settings for a library of reference signals used to train the neural network;

accessing a plurality of audio playback settings determined by the neural network based on the query;

determining a filter coefficient to apply to the audio signal based on the plurality of audio playback settings; and

applying the filter coefficient to the audio signal in a first duration.

16. The method of claim 15 , wherein the representation of the sample of the audio signal corresponds to a constant-Q transform representation of the sample of the audio signal.

17. The method of claim 15 , wherein the plurality of audio playback settings include filter settings associated with one or more filters, wherein the filter settings include one or more respective gain values, respective frequency values, or respective quality factor values associated with the sample of the audio signal.

18. The method of claim 15 , further including determining the filter coefficient to apply to the audio signal based on a type of a filter associated with the filter coefficient to be applied to the audio signal.

19. The method of claim 15 , further including applying a smoothing filter to the audio signal to reduce sharp transitions in average gain values of the audio signal between the first duration and a second duration.

20. The method of claim 15 , further including transforming the audio signal to a frequency representation of the sample of the audio signal.

Assignments (9)
RELEASE (REEL 054066 / FRAME 0064) Recorded May 11, 2023
From: CITIBANK, N.A.
To: GRACENOTE, INC.; A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063605/0001 →
RELEASE (REEL 053473 / FRAME 0001) Recorded May 11, 2023
From: CITIBANK, N.A.
To: A. C. NIELSEN COMPANY, LLC; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; THE NIELSEN COMPANY (US), LLC; NETRATINGS, LLC
Reel/Frame 063603/0001 →
SECURITY INTEREST Recorded May 8, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: ARES CAPITAL CORPORATION
Reel/Frame 063574/0632 →
SECURITY INTEREST Recorded Apr 28, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: CITIBANK, N.A.
Reel/Frame 063561/0381 →
SECURITY AGREEMENT Recorded Jan 31, 2023
From: GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE, INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC
To: BANK OF AMERICA, N.A.
Reel/Frame 063560/0547 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 22, 2022
From: MCCALLUM, MATTHEW
To: GRACENOTE, INC.
Reel/Frame 061506/0755 →
CORRECTIVE ASSIGNMENT TO CORRECT THE PATENTS LISTED ON SCHEDULE 1 RECORDED ON 6-9-2020 PREVIOUSLY RECORDED ON REEL 053473 FRAME 0001. ASSIGNOR(S) HEREBY CONFIRMS THE SUPPLEMENTAL IP SECURITY AGREEMENT. Recorded Oct 7, 2020
From: A.C. NIELSEN (ARGENTINA) S.A.; A.C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A
Reel/Frame 054066/0064 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Sep 11, 2020
From: COOVER, ROBERT; HODGES, TODD; RENNER, JOSEPH; CREMER, MARKUS; SUMMERS, CAMERON AUBREY
To: GRACENOTE, INC.
Reel/Frame 053747/0427 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Jun 9, 2020
From: A. C. NIELSEN COMPANY, LLC; ACN HOLDINGS INC.; ACNIELSEN CORPORATION; ACNIELSEN ERATINGS.COM; AFFINNOVA, INC.; ART HOLDING, L.L.C.; ATHENIAN LEASING CORPORATION; CZT/ACN TRADEMARKS, L.L.C.; EXELATE, INC.; GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC; GRACENOTE MEDIA SERVICES, LLC; NETRATINGS, LLC; NIELSEN AUDIO, INC.; NIELSEN CONSUMER INSIGHTS, INC.; NIELSEN CONSUMER NEUROSCIENCE, INC.; NIELSEN FINANCE CO.; NIELSEN FINANCE LLC; NIELSEN INTERNATIONAL HOLDINGS, INC.; NIELSEN MOBILE, LLC; NIELSEN UK FINANCE I, LLC; NMR INVESTING I, INC.; TCG DIVESTITURE INC.; TNC (US) HOLDINGS, INC.; THE NIELSEN COMPANY (US), LLC; VIZU CORPORATION; VNU MARKETING INFORMATION, INC.; NMR LICENSING ASSOCIATES, L.P.; NIELSEN HOLDING AND FINANCE B.V.; THE NIELSEN COMPANY B.V.; VNU INTERNATIONAL B.V.
To: CITIBANK, N.A.
Reel/Frame 053473/0001 →