Media Asset Recording via Audio Knowledge Graph Path Scoring
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Solution Overview
Problem
Conventional media systems struggle to record specific portions of media assets without metadata, especially during live transmissions, as they rely on metadata to identify relevant content, which is often absent.
Innovation Solution
The system analyzes audio component data using a knowledge graph to identify relevant portions by calculating a path score based on the relationships between keywords, allowing for the recording of relevant content without relying on additional metadata.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If metadata is used to identify relevant portions of media assets, then recording accuracy is improved, but the system becomes unable to process media assets without metadata
Solution Approach 1:
The patent introduces audio component data as an intermediary element between the media asset and the recording system. Instead of directly relying on metadata, the system analyzes audio components (speech, music, sound effects) to generate content descriptions that serve as a substitute for metadata, enabling the system to identify relevant portions in both metadata-rich and metadata-less scenarios
Solution Approach 2:
The patent replaces the metadata-based identification mechanism with an audio analysis-based mechanism. By using audio component analysis and content description generation, the system substitutes the traditional metadata dependency with a more versatile approach that can handle diverse media formats regardless of metadata availability
2Reliability
If the entire media asset is recorded, then no relevant content is missed, but storage space and processing time are wasted on irrelevant portions
Solution Approach 1:
The patent extracts and identifies only the relevant portions of media assets based on audio component analysis and content descriptions. By separating relevant content from irrelevant content through systematic analysis, the system records only the necessary portions, eliminating waste of storage and processing resources while maintaining completeness of important information
Solution Approach 2:
The patent divides the media asset into distinct segments based on audio component boundaries and content relevance. By segmenting the media asset and selectively recording only relevant segments, the system achieves both content completeness for important portions and efficiency by excluding irrelevant portions from recording
3Measurement precision
If audio component analysis is performed on the entire media asset, then relevant portions are accurately identified, but processing time increases
Solution Approach 1:
The patent performs preliminary audio component analysis to generate content descriptions and identify potential relevant portions before final recording decisions are made. By conducting preliminary filtering and analysis, the system reduces the scope of detailed processing needed, thereby maintaining accuracy while reducing overall processing time
Solution Approach 2:
The patent applies partial analysis to the entire media asset by focusing audio component analysis on key segments or using simplified analysis methods for initial filtering. This approach achieves sufficient relevance identification accuracy without performing exhaustive analysis on every single portion, thus balancing accuracy with processing efficiency
Data Source
AI summary
Systems and methods are presented herein for recording portions of a media asset relevant to recording criteria. A media application receives input indicating the recording criteria and identifying a first keyword. The media application accesses a data structure to identify a first node associated with the first keyword. The data structure includes the first node and a plurality of nodes connected to the first node via a plurality of paths. The media application receiving audio component data for a portion of the media asset extracts a term from the audio component data, and identifies a second node in the data structure that is associated with the extracted term. The media application calculates a path score for the portion of the media asset based on a path size in the data structure between the first node and the second node. When the score is high enough, the portion of the media asset is recorded.