Meeting Analytics System for Time Distribution Across Topic Segments
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Solution Overview
Problem
Current digital communication platforms lack analytics and metrics for time distribution of participants across topic segments in remote communication sessions, leading to inefficient use of meeting time and potential need for follow-up meetings.
Innovation Solution
A system that connects to a communication session, receives a conversation transcript with timestamps, determines the meeting type, generates topic segments, analyzes time spent by participants on each segment, and presents data on time distribution across topic segments, using AI and NLP techniques for accurate analysis and visualization.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If traditional communication platforms are used without analytics, then the system complexity remains low, but the productivity and meeting efficiency deteriorate due to lack of time distribution insights
Solution Approach 1:
The patent introduces an intermediary analytics system that sits between the communication platform and users. This intermediary automatically processes meeting transcripts, performs topic segmentation, analyzes time distribution, and generates insights without requiring users to manually analyze meetings. The intermediary handles the complexity of NLP processing, topic modeling, and data visualization, while users simply receive ready-to-use analytics reports.
Solution Approach 2:
The analytics system operates autonomously by automatically transcribing meetings, segmenting topics, analyzing participant time distribution, and generating reports without human intervention. The system self-manages the entire analytics pipeline from raw transcript data to actionable insights, eliminating the need for manual meeting analysis and reducing the cognitive load on participants.
2Measurement precision
If manual meeting analysis is performed, then the measurement precision of time distribution can be achieved, but the loss of time for analysis increases significantly
Solution Approach 1:
The patent replaces manual mechanical analysis with automated computational systems. Instead of humans manually reviewing transcripts and calculating time distributions, the system uses NLP algorithms, topic modeling, and automated speech recognition to perform the analysis. This substitution maintains high measurement precision through consistent algorithmic application while reducing analysis time from hours to minutes.
Solution Approach 2:
The system performs preliminary actions by automatically transcribing meetings and pre-processing the data during or immediately after the meeting. Topic segmentation and time distribution analysis are conducted in advance, so when participants need insights, the analysis is already complete. This preliminary automated processing eliminates the need for participants to spend time on manual analysis later.
3Loss of information
If detailed topic segmentation is implemented, then the information completeness about meeting content improves, but the device complexity for processing and presenting data increases
Solution Approach 1:
The patent applies segmentation by dividing the meeting transcript into distinct topic segments using NLP and topic modeling techniques. Each topic is identified, bounded, and labeled automatically. This segmentation preserves complete meeting content by maintaining the full transcript while organizing it into manageable thematic units, allowing users to understand the complete meeting flow without being overwhelmed by raw text volume.
Solution Approach 2:
The analytics system performs multiple functions within a single integrated platform: automatic transcription, topic segmentation, time distribution analysis, participant behavior tracking, and report generation. By consolidating these diverse functions into one universal system, the patent manages data processing complexity centrally rather than requiring separate tools for each analytical task, making the system more manageable despite its comprehensive capabilities.
Data Source
AI summary
Methods and systems provide for presenting time distributions of participants across topic segments in a communication session. In one embodiment, the system connects to a communication session with a number of participants; receives a transcript of a conversation between the participants produced during the communication session, the transcript including timestamps for each utterance of a speaking participant; determines, based on analysis of the transcript, a meeting type for the communication session; generates a number of topic segments for the conversation and respective timestamps for the topic segments; for each participant, analyzes the time spent by the participant on each of the generated topic segments in the meeting; and presents, to one or more users, data on the time distribution of participants for each topic segment and across topic segments within the conversation.