Video Content Section Identification via Indexed Text Transcripts
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Solution Overview
Problem
Users face difficulties in efficiently finding specific scenes or quotes within video content, as existing search methods are time-consuming and frustrating, especially when the title of the video is unknown or misremembered.
Innovation Solution
The development of indexed sequences of video content, generated using speech-to-text or crowd-sourced transcriptions with timestamp annotations, allows for quick identification of particular portions through text representation and machine learning classifiers, enabling efficient search and generation of custom content.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If users manually search through video content by selecting different chapters or using seek bars, then they can find specific scenes or quotes, but the search process becomes time-consuming and frustrating
Solution Approach 1:
The system performs preliminary actions by generating text representations of video content in advance and storing them in an indexed sequence. When a user searches, the system queries the pre-generated text representation instead of analyzing video content in real-time, dramatically reducing search time while maintaining accurate scene identification
Solution Approach 2:
The patent replaces manual mechanical searching (clicking seek bars, selecting chapters) with automated text-based search. Users input text queries and the system automatically matches them against the indexed text representation, substituting manual navigation with intelligent text processing
2Ease of operation
If users search for video content by title or context, then they can locate specific videos, but the process becomes more time-consuming when the title is unknown or misremembered
Solution Approach 1:
The system introduces text representation as an intermediary between video content and user queries. Instead of directly searching video files or metadata, users search through text descriptions that mediate between their intent and the actual video content, making searches more convenient and faster
Solution Approach 2:
The patent changes the search parameter from requiring exact titles or contextual knowledge to allowing flexible text queries. The system accepts various text inputs (quotes, descriptions, keywords) and matches them against the indexed text representation, reducing the time users spend remembering exact titles
3Productivity
If the system generates text representations of video content, then search efficiency improves, but the device complexity increases
Solution Approach 1:
The system extracts only the essential text representation from video content, separating this searchable information from the full video file. This extraction approach improves search productivity while limiting the added complexity to only the necessary text processing components, rather than requiring complex video analysis systems
Data Source
AI summary
Video content can be analyzed to identify particular sections of the video content. Speech to text or similar techniques can be used to obtain a transcription of the video content. The transcription can be indexed (e.g., timestamped) to the video content. Information describing how users are interacting with or consuming the video content (e.g., social media information, viewing history data, etc.) can be collected and used to identify the particular sections. Once the particular sections have been identified, other services can be provided. For example, custom trailers and summaries of the video content can be generated based on the identified sections. Additionally, the video content can be augmented to include additional information relevant to the particular sections, such as production information, actor information, or other information. The additional information can be added so as not to interfere with the important sections.