DVR Metadata Generation from Closed Captioning for Content Filtering
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Solution Overview
Problem
Users of digital video recorders (DVRs) face inconvenience and inaccuracy when manually fast-forwarding through unwanted portions of recordings, such as commercials, as they may skip desired content or resume playback in undesired sections.
Innovation Solution
The system generates metadata from text data within video streams, such as closed captioning, to identify and skip specific portions of the stream, allowing for automated filtering and accurate presentation of desired content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If manual fast forwarding is used to skip unwanted portions, then users can control playback, but accuracy and convenience deteriorate due to manual errors
Solution Approach 1:
The system automatically parses closed captioning data and identifies commercial segments without user intervention. The DVR autonomously determines which portions to skip based on text data analysis, eliminating the need for manual fast-forwarding while achieving accurate content filtering.
Solution Approach 2:
The system pre-processes the video stream during recording by parsing closed captioning data and identifying commercial portions. This preliminary analysis creates a structure that enables accurate skipping during playback without requiring real-time manual intervention.
2Measurement precision
If automated filtering using text data is implemented, then content filtering accuracy improves, but device complexity increases
Solution Approach 1:
The system introduces metadata as an intermediary layer between the video stream and the playback function. This metadata, generated from closed captioning data, serves as a simplified interface that enables accurate content filtering without requiring complex real-time analysis during playback.
Solution Approach 2:
The patent replaces manual mechanical fast-forwarding with an automated electronic system that uses text data parsing and metadata generation. This substitution eliminates manual errors while the modular metadata approach keeps system complexity manageable.
3Measurement precision
If closed captioning data is parsed to identify segments, then content identification accuracy improves, but processing time increases
Solution Approach 1:
The system performs closed captioning parsing and segment identification during the recording phase rather than during playback. This preliminary processing ensures accurate content identification is achieved beforehand, so no additional time is consumed during the actual viewing experience.
Data Source
AI summary
Various embodiments of apparatus, systems and/or methods are described for generating metadata utilized by a DVR to filter content from a video stream. A video stream is reviewed to identify portions the video stream to skip during presentation of the video stream. Text data associated with the video stream is parsed to identify a string in the text data that identifies boundaries of the portions of the video stream that are to be skipped during presentation by the DVR. The string is provided to the DVR, and the DVR utilizes the string to skip the portion of the video stream during presentation of the video stream by the DVR.