Content Management System Boundary Detection
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Solution Overview
Problem
Existing content management systems struggle to accurately detect true boundaries between content segments in broadcast or Webcast programming, often relying on approximate metadata markers that can be offset, leading to inefficiencies in content manipulation and delivery.
Innovation Solution
A content management system that receives encoded mediacast source data flows, decodes audio and metadata, detects metadata markers, and uses amplitude variations to determine a true boundary between content segments, allowing for precise splitting and modification of the content flow.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If metadata markers are used to indicate content segment boundaries, then content segmentation is automated, but the boundary detection precision deteriorates due to time offsets between metadata markers and true boundaries
Solution Approach 1:
The patent introduces an intermediary evaluation process between the metadata marker and the true boundary. An evaluation time window is established around the metadata marker timestamp, and audio analysis is performed within this window to identify the true boundary. This intermediary step reconciles the automated metadata-based segmentation with precise audio-based boundary detection.
Solution Approach 2:
The system performs preliminary action by using metadata markers to pre-identify approximate boundary locations before conducting the final precise detection. The metadata markers provide advance notice of where boundaries are likely to occur, allowing the system to focus computational resources on evaluating specific time windows rather than analyzing the entire audio stream.
2Productivity
If content boundaries are detected using approximate metadata markers, then processing speed is improved, but content manipulation accuracy deteriorates
Solution Approach 1:
The system performs partial action by analyzing only a portion of the audio stream - specifically, evaluation time windows centered around metadata marker timestamps. Rather than analyzing the entire content stream for boundaries, the system focuses computational effort on these localized windows, achieving a balance between processing speed and accuracy.
3Measurement precision
If true boundaries are detected by analyzing audio data within evaluation time windows, then boundary detection precision is improved, but system complexity increases
Solution Approach 1:
The patent applies segmentation by dividing the content stream into discrete evaluation time windows centered around metadata marker timestamps. Each window is independently analyzed for true boundary detection. This segmentation approach breaks down the complex task of continuous boundary detection into manageable, discrete analysis units.
4Productivity
If metadata markers are placed in predetermined automated locations, then content production efficiency is improved, but boundary accuracy deteriorates due to offsets from true boundaries
Solution Approach 1:
The system implements feedback by using the detected true boundaries to inform and correct the metadata marker placements. The evaluation process compares the predetermined metadata marker locations with the actually detected true boundaries, and this information can be used to refine future marker placements, creating a closed-loop system that improves accuracy while maintaining automated efficiency.
Data Source
AI summary
Systems and methods for content and program type detection, including identification of true boundaries between content segments. A broadcast provider sends a broadcast as an encoded stream. During a switch between content types, an automation system sends identifying metadata indicative of an approximate boundary between content types. A mediacast generation system receives the encoded stream of content and metadata, processes the metadata, time corrects the metadata, and slices the content on the exact boundary where the content change occurs. The mediacast generation system decodes an audio stream directly into Waveform Audio File Format (WAVE) while using an envelope follower to measure amplitude. When the system detects a metadata marker, an analyzer may look inside a buffered time window. The WAVE data may be analyzed to look for a period most likely to be the true boundary or split point between content segments. The content may then be split up on the new true boundary.