Communication Guidance System for Video Conference Cue Analysis
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Solution Overview
Problem
The limitations of non-verbal communication in video conferencing due to lack of physical presence and varying audio-visual equipment quality and internet speed hinder effective communication insights, necessitating improved real-time tracking and analysis using machine learning and AI to provide personalized feedback for optimization.
Innovation Solution
A communication guidance system that utilizes natural language processing and machine learning to analyze talking points, presenter behavior, and recipient feedback during and after video conferences, providing real-time and post-call recommendations for improvement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If video conferencing is used to conduct meetings, then productivity is improved through remote communication capability, but loss of information occurs due to limited insight into non-verbal communication cues
Solution Approach 1:
The system captures recipient feedback (verbal and non-verbal) during video conferences and provides real-time feedback to the presenter through the communication guidance system, enabling continuous improvement of communication effectiveness while maintaining remote meeting productivity
Solution Approach 2:
The communication guidance system acts as an intermediary between presenter and recipient, analyzing communication data and providing guidance recommendations that bridge the information gap caused by remote communication limitations
2Loss of information
If real-time tracking and analysis of communication metrics is implemented, then loss of information regarding communication reception is reduced, but device complexity increases due to machine learning and AI processing requirements
Solution Approach 1:
The system automatically captures, analyzes, and processes communication metrics without requiring manual intervention, using machine learning models that self-improve through continuous data processing to reduce communication information loss
Solution Approach 2:
Manual analysis of communication effectiveness is replaced with automated machine learning and AI processing, substituting human cognitive effort with computational algorithms that analyze video and audio data streams
3Productivity
If personalized feedback is provided to presenters, then communication efficiency is improved, but loss of time occurs due to the processing required to generate personalized recommendations
Solution Approach 1:
The system performs preliminary analysis of communication patterns and prepares guidance recommendations in advance during and between calls, so that personalized feedback is readily available when needed without causing delays in communication flow
Data Source
AI summary
The invention described herein relates to communication, and in particular systems and methods for understanding how communication is being received and providing real-time behavioral feedback to understand how the communication is being received, so that quantitative analysis can be done to determine KPI for optimizing video call presentations. Disclosed is a communication guidance system comprising: a non-transitory computer-readable medium; an input recognition interface; and processing circuitry operably connected to the non-transitory computer-readable medium and the input recognition interface, the processing circuitry being configured to perform the following tasks: perform an analysis of audio and video data from a user and a receiver; analyze, based on historical data, the user's communication quality; and provide feedback based on the analysis.