System and method for modifying content to broaden audience reach

Abstract

Systems and methods are disclosed for personalizing content by customizing narrative and auditory elements based on user preferences and comprehension levels. Utilizing machine learning algorithms, the described technologies adapt text and audio to match viewer interests, offering variations to the original content in style, complexity and rate. The system incorporates interactive capabilities enabling the user to switch in real time between different variations. The system utilizes dynamic user profiles to enhance personalization, with real-time adaptations based on emotional and cognitive states. In a further implementation, the system analyzes facial expressions and physiological responses, adjusting content to maintain engagement and continuously improving the content's relevance and appeal.

Description

delivery interface, one or more data storage devices, a server, wherein the system maintains a continuous stream of video content by removing duplicate segments and arranging the remaining segments in a logical sequence. In another implementation, the algorithm may use image recognition techniques to analyze keyframes and visual patterns to identify and remove visually similar segments. In a further implementation, the algorithm may employ audio analysis techniques to detect similar or identical audio segments, analyzing speech patterns, background noises, and other audio characteristics.

[0492] In one implementation, the algorithm may incorporate text analysis techniques to identify and remove redundant textual content from subtitles, captions, and on-screen text. In another implementation, the system may further comprise a natural language processing algorithm configured to respond to user comments and requests during video playback by updating the video content. In yet another implementation, the system generates a personalized stream of video content based on individual user profiles and preferences. In one implementation, the system analyzes the user's viewing history7and preferences to select and arrange non-redundant video segments that match the user's preferred style and genre. In another implementation, the content analysis module may employ advanced algorithms and machine learning techniques to refine the selection and arrangement of video segments based on user interactions, preferences, and feedback. In one implementation, the system further comprises a data aggregation module that collects video content from various sources and stores it in a centralized database In another implementation, the delivery interface may allow for real-time interaction and feedback from the user, adjusting the video stream to include relevant segments based on the user's input

Claims

CLAIMSWhat is claimed is:

1. A system incorporating machine vision capabilities for adaptive content modification, comprising: a storage device configured to receive a first video; a module- configured to analyze the first video and detect one or more humans within the data and tag each one of them, wherein the module is further configured to detect a mouth for each of the tagged humans, determine the mouth posture for each frame of the detected mouth, and extract the motion of the mouth between the determined mouth postures; a storage device configured to receive a first textual data associated with one or more dialogues of the tagged human within the video, a module configured to analyze the textual data and extract one or more syllables associated with the first textual data. a module configured to prioritize the extracted syllables using one or more of the determined mouth posture, or extracted mouth motion and generate a list wherein the syllables are arranged according to the nrioritmarion of the extracted syllables; and generate a second textual data associated with one or more dialogues of the tagged human within the video using one or more of the extracted syllables, the determined mouth posture, the extracted motion of the mouth, or the prioritized list of syllables

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