IP Library Granted Patent US 11,138,253
Granted Patent B2
US 11,138,253 · App. 16/457,429 · Granted Oct 5, 2021

Methods and apparatus to determine tags for media using multiple media features

Inventor: Morris Lee (Palm Harbor, FL)
Assignee: The Nielsen Company (US), LLC
G06F16/433G06F16/434
View Patent ↗
Loading inventors, assignments & file history…
Monitor This Case
Get email alerts when status or documents change.
Order Certified Copies
Most orders are placed with the USPTO same day — all within 24 business hours.
Order via The Patent Place →
Pre-filled with this patent's details
Quick Facts
Patent No.
US 11,138,253
App. No.
16/457,429
Filed
Jun 28, 2019
Granted
Oct 5, 2021
Kind
B2
Examiner
LE, HUNG D
Art Unit
2161
USPC
707/731
Abstract

Example methods, apparatus, systems and articles of manufacture are disclosed to determine tags for unknown media using multiple media features. Disclosed examples extract features from audio and image portions of the unknown media. Disclosed examples weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, wherein disclosed examples assign a first weight to a first feature extracted by an image-based recognition technology, and assign a second weight, different from the first weight, to a second feature extracted by an audio-based recognition technology. Disclosed examples search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media. Disclosed examples assign one or more tags from the list of suggested tags to the unknown media.

Claims (48)

1. An apparatus to tag unknown media, the apparatus comprising:

memory including computer readable instructions; and

processor circuitry to execute the instructions to at least:

extract features from audio and image portions of the unknown media;

weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, a first weight assigned to a first feature extracted by an image-based recognition technology, and a second weight, different from the first weight, assigned to a second feature extracted by an audio-based recognition technology;

search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media;

when the first feature is included in the combination of the weighted features and is assigned to a first category of a plurality of categories, limit the search in the database to pre-tagged media having category values matching the first category of the first feature; and

assign one or more tags from the list of suggested tags to the unknown media.

2. The apparatus of claim 1 , wherein the processor is to extract the features from the audio portion of the unknown media using at least one of a speech recognition engine, a sound identifier, or a song or tune identifier.

3. The apparatus of claim 1 , wherein the processor is to extract the features from the image portions of the unknown media using at least one of a logo recognition engine, an OCR engine, an object recognition engine, or a graphic recognition engine.

4. The apparatus of claim 1 , wherein the tags are approved by a user.

5. The apparatus of claim 1 , wherein the list of suggested tags includes relevancy scores indicating how relevant the tags are with respect to the unknown media, and the processor is to automatically approve a tag in the list of suggested tags when the relevancy score for the tag is above a threshold relevancy score.

6. An apparatus to tag unknown media, the apparatus comprising:

memory including computer readable instructions; and

processor circuitry to execute the instructions to at least:

extract features from audio and image portions of the unknown media;

weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, a highest weight assigned to ones of the features extracted by a logo recognition engine, a next highest weight assigned to ones of the features extracted by an optical character recognition (OCR) engine, a next highest weight assigned to ones of the features extracted by a speech recognition engine, and a lowest weight assigned to ones of the features extracted by a graphic recognition engine;

search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media; and

assign one or more tags from the list of suggested tags to the unknown media.

7. A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:

extract features from audio and image portions of the unknown media;

weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, the instructions to cause the processor to assign a first weight to a first feature extracted by an image-based recognition technology, the instructions to cause the processor to assign a second weight, different from the first weight, to a second feature extracted by an audio-based recognition technology;

search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media, when the first feature is included in the combination of the weighted features and is assigned to a first category of a plurality of categories, the instructions cause the processor to limit the search in the database to pre-tagged media having category values matching the first category of the first feature; and

assign one or more tags from the list of suggested tags to the unknown media.

8. The computer readable medium of claim 7 , wherein the instructions cause the processor to extract the features from the audio portion of the unknown media using at least one of a speech recognition engine, a sound identifier, or a song or tune identifier.

9. The computer readable medium of claim 7 , wherein the instructions cause the processor to extract the features from the image portions of the unknown media using at least one of a logo recognition engine, an OCR engine, an object recognition engine, or a graphic recognition engine.

10. The computer readable medium of claim 7 , wherein the tags are approved by a user.

11. The computer readable medium of claim 7 , wherein the list of suggested tags includes relevancy scores indicating how relevant the tags are with respect to the unknown media, and the instructions cause the processor to automatically approve a tag in the list of suggested tags when the relevancy score for the tag is above a threshold relevancy score.

12. A tangible computer readable medium comprising computer readable instructions which, when executed, cause a processor to at least:

extract features from audio and image portions of the unknown media;

weight the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, the instructions to cause the processor to assign a first weight to a first feature extracted by an image-based recognition technology, the instructions to cause the processor to assign a highest weight to ones of the features extracted by a logo recognition engine, a next highest weight to ones of the features extracted by an optical character recognition (OCR) engine, a next highest weight to ones of the features extracted by a speech recognition engine, and a lowest weight to ones of the features extracted by a graphic recognition engine;

search a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media; and

assign one or more tags from the list of suggested tags to the unknown media.

13. An apparatus to tag unknown media, the apparatus comprising:

means for extracting features from audio and image portions of the unknown media;

means for weighting the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, a first weight assigned to a first feature extracted by an image-based recognition technology, and a second weight, different from the first weight, assigned to a second feature extracted by an audio-based recognition technology;

means for searching a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media;

when the means for extracting assigns the first feature included in the combination of the weighted features to a first category of a plurality of categories, the means for searching is to limit the search in the database to pre-tagged media having category values matching the first category of the first feature; and

means for assigning one or more tags from the list of suggested tags to the unknown media.

14. The apparatus of claim 13 , wherein the means for extracting is to extract the features from the audio portion of the unknown media using at least one of a speech recognition engine, a sound identifier, or a song or tune identifier.

15. The apparatus of claim 13 , wherein the means for extracting is to extract the features from the image portions of the unknown media using at least one of a logo recognition engine, an OCR engine, an object recognition engine, or a graphic recognition engine.

16. The apparatus of claim 13 , wherein the tags are approved by a user.

17. The apparatus of claim 13 , wherein the list of suggested tags includes relevancy scores indicating how relevant the tags are with respect to the unknown media, and the means for assigning is to automatically approve a tag in the list of suggested tags when the relevancy score for the tag is above a threshold relevancy score.

18. An apparatus to tag unknown media, the apparatus comprising:

means for extracting features from audio and image portions of the unknown media;

means for weighting the features based at least partially on respective recognition technologies used to extract the features to determine corresponding weighted features, a highest weight assigned to ones of the features extracted by a logo recognition engine, a next highest weight assigned to ones of the features extracted by an optical character recognition (OCR) engine, a next highest weight assigned to ones of the features extracted by a speech recognition engine, and a lowest weight assigned to ones of the features extracted by a graphic recognition engine;

means for searching a database of pre-tagged media with a combination of the weighted features to generate a list of suggested tags for the unknown media; and

means for assigning one or more tags from the list of suggested tags to the unknown media.

Assignments (8)
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 →
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 →
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 →
ASSIGNMENT OF ASSIGNOR'S INTEREST Recorded Jul 29, 2019
From: LEE, MORRIS
To: THE NIELSEN COMPANY (US), LLC
Reel/Frame 049887/0551 →