IP Library Granted Patent US 8,805,657
Granted Patent B2
US 8,805,657 · App. 13/667,683 · Granted Aug 12, 2014

Music searching methods based on human perception

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Quick Facts
Patent No.
US 8,805,657
App. No.
13/667,683
Granted
Aug 12, 2014
Kind
B2
Abstract

A method for characterizing a musical recording as a set of scalar descriptors, each of which is based on human perception. A group of people listens to a large number of musical recordings and assigns to each one many scalar values, each value describing a characteristic of the music as judged by the human listeners. Typical scalar values include energy level, happiness, danceability, melodicness, tempo, and anger. Each of the pieces of music judged by the listeners is then computationally processed to extract a large number of parameters which characterize the electronic signal within the recording. Algorithms are empirically generated which correlate the extracted parameters with the judgments based on human perception to build a model for each of the scalars of human perception. These models can then be applied to other music which has not been judged by the group of listeners to give to each piece of music a set of scalar values based on human perception. The set of scalar values can be used to find other pieces that sound similar to humans or vary in a dimension of one of the scalars.

Claims (79)

1. A method comprising:

analyzing a musical recording by performing digital signal processing to obtain a mathematical analysis of sounds recorded in the musical recording;

calculating a first derivative parameter of the musical recording from the mathematical analysis of the sounds recorded in the musical recording;

using a computer, determining a second derivative parameter of the musical recording based on the calculated first derivative parameter of the musical recording,

the second derivative parameter being a scalar that represents an extent to which a descriptor is humanly perceivable in music represented by the musical recording;

storing the determined second derivative parameter of the musical recording as a characteristic of the musical recording;

receiving a search query that references a portion of a representative recording for which a similar recording is sought;

analyzing the portion of the representative recording by performing digital signal processing to obtain a further mathematical analysis of sounds recorded in the portion;

calculating a further first derivative parameter of the portion from the further mathematical analysis of the sounds recorded in the portion;

determining a further second derivative parameter of the portion,

the further second derivative parameter being a further scalar that represents a different extent to which the descriptor is humanly perceivable in the portion; and

in response to the search query, providing a search result that references the musical recording based on a comparison of the scalar to the further scalar.

2. The method of claim 1 , wherein:

the determining of the second derivative parameter includes multiplying the first derivative parameter by a weight factor.

3. The method of claim 2 , wherein:

the weight factor by which the first derivative parameter is multiplied is nonlinear with respect to the first derivative parameter.

4. The method of claim 2 , wherein:

the weight factor by which the first derivative parameter is multiplied is accessed from a lookup table that correlates the weight factor with the first derivative parameter.

5. The method of claim 4 , wherein:

the lookup table from which the weight factor is accessed includes values generated based on empirical data from human listeners of a plurality of musical recordings.

6. The method of claim 1 , wherein:

the calculating of the first derivative parameter is performed as part of calculating a set of first derivative parameters from the mathematical analysis of the sounds recorded in the musical recording; and

the determining of the second derivative parameter is based on the calculated set of first derivative parameters.

7. The method of claim 6 , wherein:

the determining of the second derivative parameter includes individually weighting each first derivative parameter among the set of first derivative parameters.

8. The method of claim 7 , wherein:

the weighting of each first derivative parameter is based on an empirically generated lookup table that correlates each first derivative parameter with a corresponding weight factor.

9. The method of claim 1 , wherein:

the calculated first derivative parameter represents a mathematical measurement extracted from the mathematical analysis of the sounds recorded in the musical recording,

the mathematical measurement being selected from a group consisting of harmonicity, loudness, dynamic range, rhythm strength, rhythm complexity, articulation, attack, note duration, tempo, and key.

10. The method of claim 1 , wherein:

the determined second derivative parameter quantifies the descriptor that is humanly perceivable in the music represented by the musical recording,

the descriptor being a descriptive word selected from a group consisting of happiness, anger, and danceability.

11. The method of claim 1 further comprising:

receiving a search query that specifies a range that corresponds to the descriptor that is humanly perceivable in the music;

in response to the search query, providing a search result that references the musical recording based on the scalar being within the range specified by the search query.

12. The method of claim 1 further comprising:

receiving a search query that identifies a representative recording;

accessing a further second derivative parameter of the representative recording,

the further second derivative parameter being a further scalar that represents a different extent to which the descriptor is humanly perceivable in the representative recording; and

in response to the search query, providing a search result that references the musical recording based on a comparison of the scalar to the further scalar.

13. The method of claim 1 , wherein:

the received search query includes the portion of the representative recording.

14. The method of claim 1 , wherein:

the received search query identifies a location of the portion of the representative recording; and

the analyzing of the portion of the representative recording includes accessing the portion based on the identified location.

15. The method of claim 1 , wherein:

the calculated first derivative parameter of the musical recording characterizes the sounds that are recorded in the musical recording.

16. The method of claim 1 , wherein:

the determined second derivative parameter of the musical recording characterizes the music that is represented by the musical recording.

17. The method of claim 1 , wherein:

the calculated first derivative parameter a machine-derived value extracted from the mathematical analysis of the musical recording;

the determined second derivative parameter represents the extent to which the descriptor is perceivable by a human in the music represented by the analyzed musical recording.

18. A non-transitory computer-readable medium comprising a computer program that, when executed by a computer, causes the computer to perform operations comprising:

analyzing a musical recording by performing digital signal processing to obtain a mathematical analysis of sounds recorded in the musical recording;

calculating a first derivative parameter of the musical recording from the mathematical analysis of the sounds recorded in the musical recording;

determining a second derivative parameter of the musical recording based on the calculated first derivative parameter of the musical recording,

the second derivative parameter being a scalar that represents an extent to which a descriptor is humanly perceivable in music represented by the musical recording;

storing the determined second derivative parameter of the musical recording as a characteristic of the musical recording;

receiving a search query that references a portion of a representative recording for which a similar recording is sought;

analyzing the portion of the representative recording by performing digital signal processing to obtain a further mathematical analysis of sounds recorded in the portion;

calculating a further first derivative parameter of the portion from the further mathematical analysis of the sounds recorded in the portion;

determining a further second derivative parameter of the portion,

the further second derivative parameter being a further scalar that represents a different extent to which the descriptor is humanly perceivable in the portion; and

in response to the search query, providing a search result that references the musical recording based on a comparison of the scalar to the further scalar.

19. A computer system comprising:

a computer; and

a computer program that, when executed by the computer, causes the computer to perform operations comprising:

analyzing a musical recording by performing digital signal processing to obtain a mathematical analysis of sounds recorded in the musical recording;

calculating a first derivative parameter of the musical recording from the mathematical analysis of the sounds recorded in the musical recording;

determining a second derivative parameter of the musical recording based on the calculated first derivative parameter of the musical recording,

the second derivative parameter being a scalar that represents an extent to which a descriptor is humanly perceivable in music represented by the musical recording;

storing the determined second derivative parameter of the musical recording as a characteristic of the musical recording;

receiving a search query that references a portion of a representative recording for which a similar recording is sought;

analyzing the portion of the representative recording by performing digital signal processing to obtain a further mathematical analysis of sounds recorded in the portion;

calculating a further first derivative parameter of the portion from the further mathematical analysis of the sounds recorded in the portion;

determining a further second derivative parameter of the portion,

the further second derivative parameter being a further scalar that represents a different extent to which the descriptor is humanly perceivable in the portion; and

in response to the search query, providing a search result that references the musical recording based on a comparison of the scalar to the further scalar.

Assignments (9)
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 →
RELEASE (REEL 054066 / FRAME 0064) 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 063605/0001 →
RELEASE (REEL 042262 / FRAME 0601) Recorded Oct 13, 2022
From: CITIBANK, N.A.
To: GRACENOTE, INC.; GRACENOTE DIGITAL VENTURES, LLC
Reel/Frame 061748/0001 →
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 →
SUPPLEMENTAL SECURITY AGREEMENT Recorded Apr 13, 2017
From: GRACENOTE, INC.; GRACENOTE MEDIA SERVICES, LLC; GRACENOTE DIGITAL VENTURES, LLC
To: CITIBANK, N.A., AS COLLATERAL AGENT
Reel/Frame 042262/0601 →
RELEASE OF SECURITY INTEREST IN PATENT RIGHTS Recorded Feb 8, 2017
From: JPMORGAN CHASE BANK, N.A.
To: GRACENOTE, INC.; CASTTV INC.; TRIBUNE MEDIA SERVICES, LLC; TRIBUNE DIGITAL VENTURES, LLC
Reel/Frame 041656/0804 →
SECURITY AGREEMENT Recorded Nov 13, 2014
From: GRACENOTE, INC.; TRIBUNE BROADCASTING COMPANY, LLC; TRIBUNE DIGITAL VENTURES, LLC; TRIBUNE MEDIA COMPANY
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 034231/0333 →
SECURITY INTEREST Recorded Mar 19, 2014
From: GRACENOTE, INC.
To: JPMORGAN CHASE BANK, N.A., AS COLLATERAL AGENT
Reel/Frame 032480/0272 →