US2021065249A1PendingUtilityA1

System and method for delivering personalized content based on deep learning of user emotions

Assignee: 10TALES INCPriority: Apr 7, 2003Filed: Nov 11, 2020Published: Mar 4, 2021
Est. expiryApr 7, 2023(expired)· nominal 20-yr term from priority
Inventors:David J. Russek
G06Q 10/40H04N 21/4126G06V 20/41G06F 16/58G06F 16/285H04N 21/6125G06N 20/00H04N 21/44218G06Q 30/0271G06F 16/9535H04N 21/4312G06Q 30/0277G06Q 30/00H04N 21/4788H04N 21/25883H04N 21/4532H04N 21/812G06Q 30/02G06K 9/00718G06Q 50/01G06Q 10/48G06Q 10/42G06F 16/9536
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Claims

Abstract

Disclosed are a system, method and software to associate attributes with digital media assets using deep learning. Digital media contains specific assets, such as audio, that can be replaced with other assets. The system, method and software allow for personalizing digital media content based in part on neural network analysis to learn a user's emotional state.

Claims

exact text as granted — not AI-modified
What is claimed is: 
     
         1 . A method for delivering personalized content based on learned emotions of a user, comprising:
 capturing, by a server, a plurality of user interactions performed over time with a digital media stream, wherein each user interaction is associated with a respective time point;   correlating, by the server, each user interaction to an emotional state;   learning, by a learning algorithm communicatively coupled to the server, based on the correlations, the emotional state of the user at each respective time point; and   serving, by the server, a new digital media stream based on the learned emotional states.   
     
     
         2 . The method of  claim 1 , wherein the learning utilizes an artificial intelligence method. 
     
     
         3 . The method of  claim 1 , further comprising updating a user profile with the learned emotional states. 
     
     
         4 . The method of  claim 1 , wherein the user interactions are selected from a group comprising at least one of a viewing habit, a purchase, a selection, and an answer to a question. 
     
     
         5 . The method of  claim 1 , wherein the emotional state is selected from a group comprising at least one of a happiness and sadness. 
     
     
         6 . The method of  claim 1 , wherein the emotional state is an indication of the user's affinity toward the digital media stream. 
     
     
         7 . The method of  claim 1 , wherein the emotional state is captured by an input indicating a like or dislike by a user. 
     
     
         8 . The method of  claim 1 , wherein the serving utilizes a neural network to select the new digital media stream based on the learned emotional states. 
     
     
         9 . A system for delivering personalized content based on learned emotions of a user, comprising:
 a server configured to receive a plurality of user interactions performed over time with a digital media stream;   a content server configured to store the digital media stream and transmit the digital media stream to the server;   a correlation algorithm communicatively coupled to the server, the correlation algorithm configured to correlate each user interaction to an emotional state; and   a learning module communicatively coupled to the server, the learning module configured to learn the emotional state of the user at each respective time point based on the correlations,   wherein the server is configured to serve a new digital media stream based on the learned emotional states.   
     
     
         10 . The system of  claim 9 , wherein the learning module utilizes an artificial intelligence method. 
     
     
         11 . The system of  claim 9 , wherein the server is further configured to update a user profile with the learned emotional states. 
     
     
         12 . The system of  claim 9 , wherein the user interactions are selected from a group comprising at least one of a viewing habit, a purchase, a selection, and an answer to a question. 
     
     
         13 . The system of  claim 9 , wherein the emotional state is selected from a group comprising at least one of happiness and sadness. 
     
     
         14 . The system of  claim 9 , wherein the emotional state is an indication of the user's affinity toward the digital media stream. 
     
     
         15 . The system of  claim 9 , wherein the emotional state is captured by an input by the user indicating a like or dislike. 
     
     
         16 . The system of  claim 9 , wherein the server utilizes a neural network to select the new digital media stream based on the learned emotional states. 
     
     
         17 . A method of delivering personalized content based on learned emotions of a user, comprising:
 capturing, by a server, a plurality of user interactions performed over time with a video stream, wherein each user interaction is associated with a respective time point;   correlating, by the server each user interaction to a like or a dislike;   learning, by a learning algorithm communicatively coupled to the server, based on the correlations, an emotional state of the user at each respective time point; and   serving, by the server, a new digital media stream based on the learned emotional states.   
     
     
         18 . The method of  claim 17 , wherein the learning utilizes an artificial intelligence method. 
     
     
         19 . The method of  claim 17 , wherein the video stream is selected from a group comprising at least one of a movie, a television show, and an advertisement. 
     
     
         20 . The method of  claim 17 , wherein the serving utilizes a neural network to select the new digital media stream based on the learned emotional states.

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