Automated Media Content Playback Analysis for Quality Control
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Solution Overview
Problem
The inefficiency of manual quality control (QC) processes in analyzing audio-video (AV) content, which can lead to missed defects if they occur outside predetermined spot-check intervals, necessitates the development of automated systems for media content analysis.
Innovation Solution
The implementation of automated systems and methods that analyze media content using adaptive quality control (QC) processes, which generate automation instructions based on media quality metrics and sensitivity maps to optimize playback and review efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual quality control review is performed to ensure content quality, then measurement precision is improved, but loss of time increases
Solution Approach 1:
The patent segments media content into discrete clips based on scene changes detected through automation data analysis. This segmentation allows QC review to focus on individual clips rather than entire media assets, significantly reducing review time while maintaining quality. The system divides the content into manageable units that can be independently reviewed and assessed.
Solution Approach 2:
The system performs preliminary automated analysis of media content before manual QC review by generating automation instructions from automation data. This preliminary action identifies potential quality issues and prepares the content for targeted manual review, reducing the time required for comprehensive QC while maintaining measurement precision through automated pre-screening.
2Loss of time
If spot-checks are used to reduce manual processing, then loss of time is reduced, but reliability worsens
Solution Approach 1:
The system uses feedback mechanisms where automation data from media content analysis informs the generation of automation instructions. The QC review results feed back into the system to refine future automation instructions, creating a continuous improvement loop that enhances defect detection reliability while maintaining reduced processing times through automated guidance.
Solution Approach 2:
The patent replaces manual mechanical review processes with automated systems that generate playback instructions based on analyzed automation data. This substitution uses computational algorithms to identify and flag potential defects, providing automated guidance to QC reviewers and enhancing reliability without requiring complete manual end-to-end reviews of all content.
3Reliability
If complete end-to-end review is performed to maintain quality, then reliability is improved, but productivity worsens
Solution Approach 1:
The system dynamically adjusts the review process by generating adaptive playback instructions based on analyzed automation data. The playback speed and review intensity are dynamically modified according to the detected features and quality metrics in the media content, allowing comprehensive quality assurance in critical areas while maintaining high productivity in less critical segments.
Solution Approach 2:
The patent applies local quality control by focusing detailed QC review on specific clips and segments identified through automated analysis rather than uniformly reviewing all content. The system applies different levels of review intensity to different portions of the media content based on their assessed quality risk, maintaining overall reliability while significantly improving productivity through targeted review.
Data Source
AI summary
A system includes processing hardware and a memory storing software code. The processing hardware executes the software code to receive automation data for media content having a default playback experience, analyze, using the automation data, at least one parameter of the media content, and generate, based on the analyzing, one or more automation instruction(s) for at least one portion(s) of the media content. The automation instruction(s) include at least one of: one or more bounding timestamps of the media content portion(s), an increased or reduced playback speed for the media content portion(s) relative to the default playback experience, or a variable playback speed for the media content portion(s). The software code is further executed to outputs the automation instruction(s) to a media delivery platform configured to distribute and control the quality of the media content or to a media player configured to automate playback of the media content.