Real-time Metatagging for Live Caption Search
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Solution Overview
Problem
Current captioning systems for media programs, such as television and radio, face challenges in providing real-time searchable and relevant information to users, as existing methods require users to sift through irrelevant content and lack integration of additional event-related data, making it difficult for users with hearing impairments or those seeking specific information during live events.
Innovation Solution
A method for real-time metatagging of audio and video streams, allowing users to access additional information related to events by embedding metatags into caption text, enabling users to select and link to specific information such as statistical data, events, or participants during live events, using keystrokes or automated search capabilities.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If users search through caption transcripts to find relevant information, then they can access event details, but they must sift through大量 irrelevant content which increases time and reduces efficiency
Solution Approach 1:
The patent extracts key entities (people, places, things, events) from caption transcripts and creates separate metadata tags for each. This extraction allows users to directly search for specific entities without reviewing entire transcripts, significantly reducing search time while maintaining information relevance.
Solution Approach 2:
The patent segments the continuous caption transcript into discrete, searchable entities by identifying and tagging specific people, places, things, and events. This segmentation transforms unstructured text into structured data that can be efficiently queried and filtered, eliminating the need to sift through irrelevant content.
2Ease of manufacture
If caption transcripts are provided in plain text format, then they are simple to generate, but they are not amenable to quick and efficient searching
Solution Approach 1:
The patent applies preliminary action by automatically tagging entities in caption transcripts during or immediately after the captioning process. This pre-processing step structures the data before users need to search, making subsequent search operations efficient while maintaining the simplicity of the original caption generation process.
Solution Approach 2:
The patent introduces metadata tags as an intermediary layer between the plain text caption and the search function. These tags act as a bridge that preserves the simplicity of plain text generation while enabling efficient searching through structured data markers that can be quickly processed by search algorithms.
3Measurement precision
If exact search terms are used to find specific content, then search precision is high, but variations in terminology cause relevant content to be missed
Solution Approach 1:
The patent changes the search parameter from exact text matching to entity-based tagging. By identifying and tagging entities (people, places, things, events) regardless of the specific wording used, the system maintains high search precision while becoming adaptable to terminology variations. Users can search for entities by concept rather than by exact phrase matching.
Data Source
AI summary
Methods and systems are disclosed for real-time metatagging and captioning of an event and caption extraction and analysis for such event. The method for the real-time metatagging and captioning and caption extraction and analysis of an event may include embedding metatag information in a caption file provided by a captioner. The embedded and/or extracted metatag information may allow a user to access additional information via the text of the captioned event. Data, words, or phrases can be provided by the captioner during captioning or, post-captioning, extracted from the one or more segments of the caption transcript. Metadata based on said providing and/or extracting is provided. The metadata is stored in a metadata archive, where the metadata is associated with the caption transcript.