Smart Topic Generation for Accurate Video Call Transcript Navigation
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Solution Overview
Problem
Conventional video call transcription systems struggle with inaccurate identification of relevant portions, inefficient navigation, and require excessive user interactions to locate related data across multiple transcripts and content items.
Innovation Solution
A smart topic generation system utilizing a large language model, context transformer engine, and smart topic agent to automatically generate actionable, standalone smart topics from video call transcripts, summarizing and surfacing relevant content with minimal user input.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Extent of automation
If conventional natural language processing systems are used to generate transcripts and identify topic portions, then transcript generation is achieved, but accuracy in identifying relevant portions and related digital content deteriorates
Solution Approach 1:
The patent introduces an intermediary system that connects the transcript generation process with topic identification and digital content retrieval. This intermediary layer processes the generated transcripts through additional analysis steps to accurately identify topic portions and their corresponding digital content, resolving the accuracy deterioration caused by direct conventional NLP approaches
Solution Approach 2:
The patent replaces conventional mechanical natural language processing systems with an enhanced system that incorporates multiple processing stages including transcript generation, topic portion identification, and digital content association. This substitution improves measurement precision by using more sophisticated analysis methods beyond basic NLP
2Ease of operation
If conventional systems provide transcript searching and navigation interfaces, then users can access transcript data, but navigational efficiency deteriorates due to excessive user interactions required
Solution Approach 1:
The patent applies preliminary action by pre-identifying and organizing topic portions and their corresponding digital content before user interaction. The system prepares structured topic-based indexes and associations in advance, allowing users to directly access relevant content without excessive navigation or search interactions
Solution Approach 2:
The patent creates a universal interface that combines transcript viewing, topic identification, and digital content access into a single integrated system. This multi-functional interface eliminates the need for separate applications and excessive navigational steps, improving ease of operation while reducing time loss
3Adaptability or versatility
If separate interfaces and applications are used for viewing transcripts, aggregating data, and searching content items, then comprehensive functionality is achieved, but device complexity deteriorates
Solution Approach 1:
The patent merges multiple separate functions (transcript viewing, data aggregation, content searching) into a single integrated interface. This combining of previously separate applications and interfaces reduces device complexity while maintaining comprehensive functionality through unified access points
4Reliability
If conventional systems require multiple navigational and search inputs to locate related portions across transcripts, then thorough searching is achieved, but productivity deteriorates
Solution Approach 1:
The patent performs preliminary organization of transcript data into topic-based structures with associated digital content before user queries. This pre-processing enables direct retrieval of relevant portions without requiring multiple sequential search inputs, maintaining search thoroughness while dramatically improving productivity
Solution Approach 2:
The patent implements feedback mechanisms where the system learns from user interactions and search patterns to improve topic identification and content association. This feedback loop enhances search thoroughness over time while reducing the number of inputs needed, thereby improving productivity
Data Source
AI summary
The present disclosure relates to systems, non-transitory computer-readable media, and methods for utilizing a context transformer engine, a smart topic agent, and a large language model to generate a smart topic output. In particular, in one or more embodiments, the disclosed systems generate a smart topic output from a transcript of a video call. In some embodiments, the disclosed systems provide a smart topic interface that provides the smart topic output on a client device and receives selections of smart topic elements. In one or more embodiments, the disclosed systems generate a combined smart topic from transcripts of video calls in which client devices that participated are associated with a collaborating user account group.