Meeting Summary Generation via Transcript-Note Correlation
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current methods for capturing and summarizing meeting content are inefficient, as they require significant time and attention from participants, are difficult to share, and often lack a comprehensive view of all participants' viewpoints, leading to inaccurate importance placement of topics.
Innovation Solution
An information handling system that processes notes from multiple users and devices using algorithms for key item detection, sentiment analysis, and deep learning to generate a meeting summary, correlating meeting agendas, transcripts, and notes to determine action item importance and topic relevance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If meeting participants take notes on all matters discussed, then a complete record of the meeting is captured, but the participant's time and attention are significantly consumed, decreasing their opportunity to participate in the ongoing discussion
Solution Approach 1:
The system performs preliminary actions by automatically transcribing the meeting audio into text and pre-processing the content through NLP algorithms to identify potential action items, decisions, and key topics before human review. This preliminary processing reduces the time participants need to spend on note-taking while ensuring comprehensive capture of meeting content.
Solution Approach 2:
The system enables self-service by automatically generating meeting summaries, identifying action items, and organizing meeting content without requiring manual note-taking from participants. The AI-driven system serves itself by transcribing, analyzing, and structuring the meeting data, freeing participants to focus on active participation rather than documentation.
2Loss of information
If handwritten notes are used to capture meeting content, then a personal record is created, but the notes are difficult to share with other participants or non-participants
Solution Approach 1:
The system creates digital copies of the meeting content through automatic transcription of audio into text. These digital copies can be easily replicated, distributed, and shared with any number of participants or non-participants without degradation of quality or additional effort, eliminating the sharing difficulties associated with handwritten notes.
Solution Approach 2:
The system replaces the mechanical process of handwriting notes with automated computational processes including audio transcription, natural language processing, and algorithmic analysis. This substitution transforms the note-taking process from a manual, hard-to-share format to a digital, easily distributable format that can be accessed by multiple users simultaneously.
3Device complexity
If a single participant's notes are used to determine importance of topics, then the process is simple, but the importance placement may be inaccurate as it reflects only one viewpoint
Solution Approach 1:
The system merges multiple perspectives by analyzing transcripts and notes from all meeting participants rather than relying on a single viewpoint. By combining and analyzing all available data sources through NLP algorithms, the system achieves more accurate determination of topic importance and action item priority while maintaining computational efficiency through automated processing.
Data Source
AI summary
A method and apparatus for automatically generating a meeting summary is disclosed herein. Meeting audio is recorded and converted into a text-based transcript. Handwritten meeting notes are converted into notes text. The transcript and notes text are correlated to provide correlated meeting text. Meeting topics are determined from the correlated meeting text. A meeting summary is generated from the meeting topics.