IP Library › Granted Patent US 12713108
Granted Patent B2
US 12713108 · App. 18/663,999 · Granted Aug 18, 2026

Dynamic advertisement placement based on content understanding and user data

Inventors: Snehal Karia (Fremont, CA); Sunil Ramesh (Saratoga, CA); Alexander P. Hill (Danville, CA); Andrew Adams (Bryn Mawr, PA)
Assignee: Roku, Inc.
H04N21/812H04N21/2187H04N21/233H04N21/23412H04N21/44213
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Quick Facts
Patent No.
US 12713108
App. No.
18/663,999
Granted
Aug 18, 2026
Kind
B2
Abstract

Aspects of the disclosed technology provide solutions for dynamically placing an advertisement within media content based on content understanding and/or user data. An example method can include receiving live media content, which captures a live event, analyzing the live media content to identify one or more attributes associated with the live event, and accessing user data associated with a user device displaying the live media content. The example method can further include determining a time at which an advertisement is to be inserted within the live media content based on at least one of the one or more attributes or the user data.

Claims (49)

1 . A system comprising:

one or more memories; and

at least one processor coupled to the one or more memories and configured to perform operations comprising:

receiving live media content, the live media content capturing a live event;

identifying one or more attributes associated with the live event based on the live media content;

accessing user data associated with a user device displaying the live media content;

determining, for one or more time intervals of the live event, a corresponding predicted activity level, based on the one or more attributes and the user data; and

determining a time interval of the one or more time intervals at which an advertisement is to be inserted within the live media content based on the predicted activity level of each of the one or more time intervals.

2 . The system of claim 1 , wherein the at least one processor is configured to perform operations comprising:

determining a display size of the advertisement, for when the advertisement is presented on the user device, based on at least one of the one or more attributes or the user data.

3 . The system of claim 2 , wherein the at least one processor is configured to perform operations comprising:

adjusting the display size of the advertisement relative to a display size of the live media content, while the advertisement is displayed on the user device, based on a confidence level of the predicted activity level of the time interval.

4 . The system of claim 1 , wherein the at least one processor is configured to perform operations comprising:

determining a volume level associated with the advertisement relative to a volume level of the live media content based on at least one of the one or more attributes or the user data.

5 . The system of claim 1 , wherein the at least one processor is configured to perform operations comprising:

determining a context of the advertisement based on at least one of the one or more attributes associated with the live event or the user data.

6 . The system of claim 1 , wherein the at least one processor is configured to perform operations comprising:

determining a duration of the advertisement or a number of advertisements to be inserted within the live media content based on at least one of the one or more attributes associated with the live event or the user data.

7 . The system of claim 1 , wherein the time in the live media content for the advertisement to be inserted is determined using a machine learning model.

8 . The system of claim 1 , wherein analyzing the live media content to identify the one or more attributes associated with the live media content comprises:

generating, based on one or more signals in the live media content, one or more event captions representing information about the live media content, wherein the one or more signals comprise a visual signal, an audio signal, or a closed caption signal.

9 . The system of claim 1 , wherein the one or more attributes associated with the live event include at least one of a geographic location of the live event, a type or genre of the live event, a venue of the live event, players or participants in the live event, an audience of the live event, sponsors of the live event, statistics relating to the live event, a progress of the live event, or rules of the live event.

10 . The system of claim 1 , wherein the user data includes at least one of user preferences, viewing history, demographics, or social media data.

11 . A method comprising:

receiving live media content, the live media content capturing a live event;

identifying one or more attributes associated with the live event based on the live media content;

accessing user data associated with a user device displaying the live media content;

determining, for one or more time intervals of the live event, a corresponding predicted activity level, based on the one or more attributes and the user data; and

determining a time interval of the one or more time intervals at which an advertisement is to be inserted within the live media content based on the predicted activity level of each of the one or more time intervals.

12 . The method of claim 11 , further comprising:

determining a display size of the advertisement, for when the advertisement is presented on the user device, based on at least one of the one or more attributes or the user data.

13 . The method of claim 12 , further comprising:

adjusting the display size of the advertisement relative to a display size of the live media content, while the advertisement is displayed on the user device, based on a confidence level of the predicted activity level of the time interval.

14 . The method of claim 11 , further comprising:

determining a volume level associated with the advertisement relative to a volume level of the live media content based on at least one of the one or more attributes or the user data.

15 . The method of claim 11 , further comprising:

determining a context of the advertisement based on at least one of the one or more attributes associated with the live event or the user data.

16 . The method of claim 11 , further comprising:

determining a duration of the advertisement or a number of advertisements to be inserted within the live media content based on at least one of the one or more attributes associated with the live event or the user data.

17 . The method of claim 11 , wherein the time in the live media content for the advertisement to be inserted is determined using a machine learning model.

18 . The method of claim 11 , wherein analyzing the live media content to identify the one or more attributes associated with the live media content comprises:

generating, based on one or more signals in the live media content, one or more event captions representing information about the live media content, wherein the one or more signals comprise a visual signal, an audio signal, or a closed caption signal.

19 . The method of claim 11 , wherein the one or more attributes associated with the live event include at least one of a geographic location of the live event, a type or genre of the live event, a venue of the live event, players or participants in the live event, an audience of the live event, sponsors of the live event, statistics relating to the live event, a progress of the live event, or rules of the live event.

20 . A non-transitory computer-readable medium having instructions stored thereon that, when executed by at least one computing device, cause the at least one computing device to perform operations comprising:

receiving live media content, the live media content capturing a live event;

identifying one or more attributes associated with the live event based on the live media content;

accessing user data associated with a user device displaying the live media content;

determining, for one or more time intervals of the live event, a corresponding predicted activity level, based on the one or more attributes and the user data; and

determining a time interval of the one or more time intervals at which an advertisement is to be inserted within the live media content based on the predicted activity level of each of the one or more time interval.