Real-Time Closed Caption Extraction for Streaming Ad Analytics
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Solution Overview
Problem
Current systems lack the ability to monitor and analyze multiple TV channels in real-time for specific keywords or concepts, and fail to efficiently deliver alerts and data over lower-speed networks, while also limiting the capability to extract and index closed captions for comprehensive search and analytics.
Innovation Solution
The development of methods and systems for real-time or near-real-time extraction of closed captions from video broadcasts, encoding and embedding Advertisement Tag Codes, and providing alerts based on keywords or concepts, enabling users to index and assemble relevant audio and video segments, with capabilities for distributed or centralized operation across various devices, including PCs and mobile devices. This includes embedding Advertisement Tag Codes in video streams for automatic data collection and correlation with other media sources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If real-time extraction of closed captions is implemented, then monitoring capability is improved, but processing time and system complexity increase
Solution Approach 1:
The system segments the video stream into discrete caption frames, extracting and processing only the text data at specific time intervals rather than continuously analyzing the entire video stream. This allows real-time monitoring while reducing processing time by focusing computation only on the caption data rather than the complete video content.
Solution Approach 2:
The system extracts only the closed caption text data from the video stream, separating the relevant information (captions) from the irrelevant data (video audio and visual content). This extraction approach enables real-time monitoring of keyword concepts while minimizing processing time by working only with the extracted text rather than the complete video stream.
2Adaptability or versatility
If multiple channels are monitored simultaneously, then search capability is improved, but network bandwidth requirements increase
Solution Approach 1:
The system extracts and transmits only the closed caption text data from multiple channels rather than the complete video streams. This extraction reduces the quantity of data that must be transmitted over the network, enabling monitoring of multiple channels simultaneously while minimizing bandwidth requirements by sending only the relevant text information.
Solution Approach 2:
The system processes and transmits caption data in segmented frames rather than continuous streams. This segmentation allows the system to monitor multiple channels simultaneously while reducing network bandwidth requirements by transmitting only the discrete caption information at specific time intervals rather than continuous video data.
3Loss of information
If keyword search and alerting are implemented, then information retrieval is improved, but system complexity increases
Solution Approach 1:
The system automatically extracts, indexes, and searches through closed caption data without requiring manual intervention. The automated keyword search and alerting mechanisms perform information retrieval functions independently, reducing the need for complex manual processing while improving information retrieval capabilities through automated text analysis and pattern matching.
Data Source
AI summary
System and methods for finding and accessing target content from audio and video content sources, including means and methods for extracting captions from audio and video content sources; searching the captions for a mention of at least one target; extracting audio and video segments relating to the at least one target; delivering extracted audio and video segments to a user device; analyzing the results for target content; thereby providing a method for quickly finding and accessing desired audio and video content from a large number of sources.