IP Library Granted Patent US 12681984
Granted Patent B2
US 12681984 · App. 19/029,473 · Granted Jul 14, 2026

Audiovisual content curation system

Inventors: Peter C. DiMaria (New York, NY); Andrew Silverman (New York, NY)
Assignee: Gracenote, Inc.
G06F16/61G06F16/686
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Quick Facts
Patent No.
US 12681984
App. No.
19/029,473
Granted
Jul 14, 2026
Kind
B2
Abstract

Systems and methods are provided for filtering at least one media content catalog based on criteria for a station library to generate a first list of candidate tracks for the station library, combining a similarity score and a popularity score for each track of the first list of candidate tracks to generate a total score for each track of the first list of candidate tracks, generating a list of top ranked tracks for the first genre, and returning the list of top ranked tracks of the first genre as part of the station library.

Claims (34)

1 . A tangible, non-transitory machine-readable medium having stored thereon instructions that, when executed, cause one or more processors to perform a set of operations comprising:

generating a similarity score for a plurality of tracks in a list of candidate tracks, wherein generating the similarity scores comprises determining, for each track in the plurality of tracks, correlation values between a first criteria and a second criteria of the plurality of tracks in the list of candidate tracks;

determining popularity scores for each for each track in the plurality of tracks;

generating a total score for each track of the plurality of tracks, wherein generating a total score comprises combining, for each track of the plurality of tracks, the similarity score and the popularity score associated with each track; and

generating a list of top ranked tracks, wherein generating the list of top ranked tracks is based on the total score for each track in the plurality of tracks.

2 . The tangible, non-transitory machine-readable medium of claim 1 , wherein the correlation values are compared to a threshold.

3 . The tangible, non-transitory machine-readable medium of claim 1 , wherein generating a list of top ranked tracks is based on combining a similarity score and a popularity score associated with for each track in the plurality of tracks to generate total scores for each track in the plurality of tracks.

4 . The tangible, non-transitory machine-readable medium of claim 1 , wherein one or more tracks in the list of candidate tracks comprises one or more descriptors indicating one or more of the following: a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

5 . The tangible, non-transitory machine-readable medium of claim 4 , wherein the set of operations further comprise transmitting instructions that cause a computing device to display, via a graphical user interface, for one or more of the plurality of tracks, a graphical indication of one or more of the following: a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

6 . The tangible, non-transitory machine-readable medium of claim 5 , wherein the computing device is a client computing device.

7 . The tangible, non-transitory machine-readable medium of claim 1 , wherein generating the similarity score for each of the tracks in the list of candidate tracks further comprises comparing the first criteria and qualities associated with each track.

8 . The tangible, non-transitory machine-readable medium of claim 1 , wherein the set of operations further comprise transmitting instructions that cause a computing device to display, via a graphical user interface, a graphical indication of the list of top ranked tracks.

9 . The tangible, non-transitory machine-readable medium of claim 1 , wherein the set of operations further comprises determining a the list of candidate tracks to be added to a station library based on the first criteria, and wherein the first criteria comprises one or more of the following: a genre, a mood, an era, an origin, an artist type, an artist profile, a catalogue identifier, or a percent mix.

10 . The tangible, non-transitory machine-readable medium of claim 9 , wherein the station library includes a list of audio tracks and wherein the list of audio tracks comprises the list of candidate tracks.

11 . The tangible, non-transitory machine-readable medium of claim 9 , wherein the set of operations further comprises adding the list of top ranked tracks to the station library.

12 . A computer-implemented method comprising:

generating a similarity score for a plurality of tracks in a list of candidate tracks, wherein generating the similarity scores comprises determining, for each track in the plurality of tracks, correlation values between a first criteria and a second criteria of the plurality of tracks in the list of candidate tracks;

determining popularity scores for each for each track in the plurality of tracks;

generating a total score for each track of the plurality of tracks, wherein generating a total score comprises combining, for each track of the plurality of tracks, the similarity score and the popularity score associated with each track; and

generating a list of top ranked tracks, wherein generating the list of top ranked tracks is based on the total score for each track in the plurality of tracks.

13 . The computer-implemented method of claim 12 , wherein the correlation values are compared to a threshold.

14 . The computer-implemented method of claim 12 , wherein generating a list of top ranked tracks is based on combining a similarity score and a popularity score associated with for each track in the plurality of tracks to generate total scores for each track in the plurality of tracks.

15 . The computer-implemented method of claim 12 , wherein one or more tracks in the list of candidate tracks comprises one or more descriptors indicating one or more of the following: a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

16 . The computer-implemented method of claim 15 , further comprising transmitting instructions that cause a computing device to display, via a graphical user interface, for one or more of the plurality of tracks, a graphical indication of one or more of the following: a rank, a title, an artist, an artist type, an album, a genre, a mood, an era, an origin, a popularity score, a similarity score, a total score, a catalogue identifier, or an external identifier.

17 . A computer-implemented method of claim 12 , wherein generating the similarity score for each of the tracks in the list of candidate tracks further comprises comparing the first criteria and qualities associated with each track.

18 . The computer-implemented method of claim 12 , further comprising transmitting instructions that cause a computing device to display, via a graphical user interface, a graphical indication of the list of top ranked tracks.

19 . The computer-implemented method of claim 12 , further comprising determining a the list of candidate tracks to be added to a station library based on the first criteria and adding the list of top ranked tracks to the station library.

20 . A computing device comprising:

one or more processors; and

a tangible, non-transitory machine-readable medium having stored thereon instructions that, when executed, cause the one or more processors to perform a set of operations comprising:

generating a similarity score for a plurality of tracks in a list of candidate tracks, wherein generating the similarity scores comprises determining, for each track in the plurality of tracks, correlation values between a first criteria and a second criteria of the plurality of tracks in the list of candidate tracks;

determining popularity scores for each for each track in the plurality of tracks;

generating a total score for each track of the plurality of tracks, wherein generating a total score comprises combining, for each track of the plurality of tracks, the similarity score and the popularity score associated with each track; and

generating a list of top ranked tracks, wherein generating the list of top ranked tracks is based on the total score for each track in the plurality of tracks.