Transcript-Based Video Segmentation by Narrative Theme for Fast Retrieval
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Solution Overview
Problem
Existing media processing technologies struggle with efficiently segmenting and indexing information-rich content due to the massive amount of data, often relying on manual methods that provide insufficient or inaccurate summaries, making it difficult for users to find relevant content.
Innovation Solution
A system utilizing computing devices to segment media content by narrative themes through analyzing textual transcripts, calculating relevance intervals for terms, and creating searchable indexes to facilitate efficient retrieval of segments based on themes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If manual methods are used to generate textual descriptions of media segments, then content accuracy can be maintained through human judgment, but processing speed and scalability deteriorate due to the massive amount of information requiring manual analysis
Solution Approach 1:
The patent introduces an automated processing system that acts as an intermediary between the raw media content and the user search queries. This system uses computational algorithms to analyze transcripts, identify themes, and generate segment descriptions automatically, replacing manual human analysis while maintaining acceptable accuracy through structured processing methods
Solution Approach 2:
The patent replaces the mechanical manual process of human analysts reading and summarizing content with an automated computational system. The system uses text processing algorithms, theme identification methods, and automated segmentation to perform functions previously requiring human cognitive effort, thereby dramatically increasing processing speed while maintaining scalability
2Reliability
If detailed textual descriptions are provided for each media segment to improve search accuracy, then user search capability is enhanced, but the complexity of processing and storing this information increases significantly
Solution Approach 1:
The patent divides the media content into discrete segments based on identified themes and narrative structures. Each segment is processed independently with its own metadata and description, allowing the system to manage complexity by breaking down large media files into smaller, more manageable units that can be indexed and searched separately
Solution Approach 2:
The patent transforms unstructured media content into structured data with specific parameters including theme identifiers, time stamps, segment boundaries, and standardized descriptions. This parameterization converts complex unstructured information into organized data fields that are easier to process, store, and retrieve, reducing overall system complexity while improving search accuracy
3Adaptability or versatility
If comprehensive indexing of all media content is performed to enable thorough retrieval, then content discoverability is improved, but the time and resources required for indexing increase dramatically
Solution Approach 1:
The patent performs preliminary processing of media content during ingestion, creating theme-based segments and generating descriptions in advance rather than waiting for search requests. This preliminary indexing allows the system to have content ready for rapid retrieval, reducing the time penalty associated with comprehensive indexing by spreading the processing work across content ingestion events
Solution Approach 2:
The patent implements selective indexing that focuses on the most relevant and search-worthy portions of media content based on identified themes and narrative elements. Rather than uniformly processing all content with equal detail, the system applies partial processing to less important segments while maintaining detailed indexing for high-value content, optimizing the balance between discoverability and processing resources
Data Source
AI summary
Content items may be segmented and labeled by a theme to provide information, such as audio or video, with greater functionality, accuracy and speed. The segments and other related information may be stored and made accessible to users through, for example, a search service and/or an on-demand service. Also provided is automatic segmentation that may include any one of receiving a textual description of a content item, determining themes within the textual description, determining relevance intervals corresponding to terms of the theme, filtering and/or merging the relevance intervals, and determining a total interval for each theme that represents one or more contextually-coherent segments of the content item.