Patent ID: 11934921
Assignee: INTERNATIONAL BUSINESS MACHINES CORPORATION
Field: Computer technology (Electrical engineering)
Classification: CPC G | IPC G

Claim 9:
10. A computer implemented method comprising:
training a machine learning model for predicting a rating in respective content rating systems based on training data including previously rated contents associated with the respective content rating systems, wherein the machine learning model includes a plurality of maturity classifiers corresponding to individual features of the previously rated contents and rating rules respective to the content rating systems;
obtaining an input content and an objective indicating how to process the input contents, wherein the input content includes at least a video stream and an audio stream;
extracting linguistic features, visual features, and audio features of the input content by use of respective content analysis tools, wherein the extracting the linguistic features includes subjecting text to natural language processing, wherein the extracting the visual features includes processing the video stream, and wherein the extracting the audio features includes processing the audio stream; and
classifying the linguistic features, the visual features, and the audio features of the input content as extracted by tagging with respective maturity classifiers of the machine learning model so that the linguistic features of the input content are tagged with a linguistic feature maturity classifier, the visual features of the input content are tagged with a visual feature maturity classifier, and the audio features of the input content are tagged with an audio feature maturity classifier, wherein the method includes the training the machine learning model for predicting a rating in respective content rating systems based on training data including the previously rated contents associated with the respective content rating systems, wherein the machine learning model includes the plurality of maturity classifiers corresponding to individual features of the previously rated contents; the obtaining the input content and the objective indicating how to process the input contents; the extracting the linguistic, visual, and audio features of the input content by use of the respective content analysis tools; classifying the features of the input content as extracted by the tagging with respective maturity classifiers of the machine learning model; obtaining, from a viewer device, real-time viewer feedback at a location on in-viewing content, wherein the machine learning model is trained with viewer profiles for the location; determining one of the content rating systems in the training data as being applicable at the location; determining a viewer maturity level based on the real-time viewer feedback and the viewer profiles for the location, predicting a rating of the in-viewing content based on the one content rating system applicable for the location; ascertaining that the viewer maturity level of the in-viewing content is less mature than the rating of the in-viewing content as predicted; transforming the in-viewing content to a viewer maturity oriented content by auto-cutting features that are associated with maturity classifiers that contributed to the rating of the in-viewing content that is more mature than the viewer maturity level in the one content rating system applicable for the location; and auto-cutting, in real time, the in-viewing content to the viewer using the auto-cutting features.