Video Metadata Tagging for More Accurate Semantic Search
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Solution Overview
Problem
Existing digital media search systems, relying on third-party metadata, often fail to capture the full essence of digital media content, leading to inaccurate search results due to limited and incomplete metadata.
Innovation Solution
Enhance digital media databases by extracting audio and closed caption data from videos, using a large language model to generate additional tags, and employing multidimensional vectors to represent metadata, enabling semantic searches and proactive video suggestions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of manufacture
If third-party metadata is used for digital media search, then search system implementation is simplified, but search accuracy deteriorates due to limited and incomplete metadata
Solution Approach 1:
The system performs preliminary extraction of audio and closed caption data from videos before search operations. This pre-processing step prepares comprehensive metadata in advance, enabling accurate semantic search without requiring complex real-time processing during user queries.
Solution Approach 2:
A large language model serves as an intermediary component that processes extracted audio and closed caption data to generate comprehensive metadata tags. This intermediary layer transforms raw media data into structured, semantically rich metadata that enhances search accuracy while maintaining system simplicity.
2Speed
If traditional keyword search is used, then search speed is fast, but search results are inaccurate due to limited metadata coverage
Solution Approach 1:
The patent replaces traditional mechanical keyword-matching search mechanisms with a semantic search system using multidimensional vectors and large language models. This substitution enables the system to understand and match the essence of content rather than relying solely on literal keyword matches, improving accuracy while maintaining speed through efficient vector-based retrieval.
3Measurement precision
If comprehensive metadata extraction is performed, then search accuracy is improved, but processing time increases
Solution Approach 1:
The system extracts audio and closed caption data and generates metadata tags in advance during a preliminary processing phase. This pre-extraction approach completes the time-consuming analysis before search operations, ensuring accurate search results without adding delay to user query response time.
Data Source
AI summary
The system obtains, from a database storing multiple videos, a video including associated metadata. The database storing multiple videos is configured to support a first search using the metadata. The system obtains, from the video, an audio and a closed caption data, and provides the audio, the closed caption data, the metadata, and a prompt to an artificial intelligence. The prompt requests multiple tags based on the audio, the closed caption data, and the metadata. A tag among the multiple tags indicates a property associated with the video. The system stores the multiple tags in the database by adding the multiple tags to the metadata to obtain new metadata. The system enables a second search of the multiple videos stored in the database by searching the new metadata, where the second search provides more accurate results than the first search.