Media Recording Salient Event Replacement for Skip Reduction
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Solution Overview
Problem
Current technologies lack the ability to effectively analyze and summarize user interaction behaviors with media recordings, such as skipping, to identify the underlying reasons for these actions, which hinders the creation of improved media content that minimizes user interactions and optimizes computing resource usage.
Innovation Solution
A computing device that determines the probability of specific salient events causing user actions like skipping, replacing these events with less likely ones to reduce user interactions, thereby optimizing computing resource usage by analyzing and mapping musical components in time and providing recommendations for derivative media recordings.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If media recordings contain salient events that attract user attention, then user engagement with content increases, but user skip actions increase causing wasted computing resources
Solution Approach 1:
The patent segments media recordings into distinct events with different salience levels. By identifying and separating high-salience events that cause skips from other content, the system can selectively modify or remove problematic segments while preserving engaging content, thus reducing skips without sacrificing overall user engagement.
Solution Approach 2:
The system changes the salience parameter of specific events by applying transformations such as volume adjustments, pitch shifts, or temporal modifications. This allows high-salience events that trigger skips to be attenuated or modified, reducing their harmful impact while maintaining the overall structure and engagement value of the media recording.
2Measurement precision
If the system analyzes user behavior in detail to identify skip causes, then content improvement accuracy increases, but processing complexity increases
Solution Approach 1:
The patent extracts only the most relevant features from user behavior data—specifically timing and type of skip actions—rather than analyzing all possible behavioral parameters. This extraction of essential information maintains analysis accuracy while significantly reducing processing complexity and computational requirements.
Solution Approach 2:
The system performs partial analysis by focusing only on the portion of user behavior data that is most predictive of skips, rather than comprehensively analyzing all aspects of user interaction. This partial action approach achieves sufficient precision for the task without the overhead of complete behavioral analysis.
3Productivity
If the system provides detailed recommendations to creators, then content improvement effectiveness increases, but information processing requirements increase
Solution Approach 1:
The patent provides localized recommendations that focus on specific problematic events and time segments rather than offering global, comprehensive suggestions. By targeting only the specific events that caused skips with tailored recommendations, the system maintains high effectiveness while reducing the overall volume of information that needs to be processed and communicated to creators.
Data Source
AI summary
A computing device comprising a display screen, the computing device being configured to decompose a media recording into a plurality of media recording salient events, apply each of the media recording salient events to a reinforcement model, display on the display screen (i) a mapping of the plurality of media recording salient events and (ii) for at least one of the plurality of media recording salient events, at least one selectable next best action, the computing device further configured to replace at least one of the plurality of media recording salient events with at least one selectable next best action to create a derivative media recording including at least one replacement media recording action.