Temporally-Correlated Conference Metadata Indexing
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Solution Overview
Problem
Existing conference recording technologies face challenges in efficiently locating specific portions of recordings related to particular topics or activities, as manual tagging is time-consuming, and automated systems are not robust or scalable enough for large-scale deployments, leading to ineffective search results and tedious scanning through long video streams.
Innovation Solution
A system that captures and correlates activities during conferences with temporally-specific metadata, allowing users to index and jump directly to relevant sections within recordings, using activity streams and transcoding services to generate and store metadata alongside conference transcripts.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual tagging is used to generate metadata for conference recordings, then the metadata can be accurately associated with specific topics and activities, but the process becomes extremely time-consuming and virtually infeasible for large sets of conference recordings
Solution Approach 1:
The patent replaces manual mechanical tagging with automated computer-based analysis systems that use speech recognition, optical character recognition, and natural language processing to generate metadata automatically, eliminating the time-consuming manual process while maintaining accuracy
Solution Approach 2:
The system enables self-service metadata generation by automatically analyzing conference recording content and generating relevant metadata without requiring human intervention, allowing the system to serve itself in the metadata creation process
2Productivity
If automated metadata generation systems are deployed at large scale, then processing time is reduced, but the systems lack robustness and scalability for large-scale deployments
Solution Approach 1:
The patent segments the automated metadata generation process into multiple independent analysis modules (speech recognition, optical character recognition, natural language processing) that can operate independently and be scaled individually, improving both productivity and robustness through modular architecture
Solution Approach 2:
The system implements multi-functional automated analysis capabilities that can handle various types of conference recordings and generate multiple types of metadata simultaneously, enhancing scalability and robustness across different deployment scenarios
3Ease of operation
If users search through conference recordings based on file metadata alone, then the search process is simple, but the search results are ineffective when users are interested in specific topics without knowing when or in which meetings the topics were discussed
Solution Approach 1:
The patent applies preliminary action by automatically generating comprehensive metadata including topic keywords and temporal information before users perform searches, so that when users search for topics, the system already has the necessary information to provide effective results without requiring users to know specific meeting times
Solution Approach 2:
The system introduces metadata as an intermediary layer between simple file metadata and the actual conference content, providing topic keywords and temporal correlations that bridge the gap between simple search operations and comprehensive topic location information
4Productivity
If users locate conference recordings through automatically-generated metadata, then search capability is improved, but users still must scan through long video streams to identify relevant sections, which is tedious and time-consuming
Solution Approach 1:
The patent adds a temporal dimension to metadata by correlating topic keywords with specific time offsets in the conference recordings, transforming the search from a two-dimensional process (finding the right file) to a three-dimensional process (finding the right file, topic, and time section), thereby eliminating the need for manual scanning through video streams
Data Source
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AI summary
Techniques are provided for capturing events and activities that occur during a conference, generating metadata related to the events, and correlating the metadata with specific points in time, within the conference, at which the corresponding events occurred. The resulting temporally-correlated event metadata may be stored as part of the conference recording, or separate from the conference recording. Once the temporally-correlated event metadata has been stored for a conference, the conference may be indexed based on the metadata. The index may then be used to not only to locate a conference that satisfies specified search criteria, but to identify the points or snippets, within the conference, that correspond to the search criteria.