Audio Sentiment Analysis for Online Meeting Moderation
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Solution Overview
Problem
Existing solutions for maintaining order in online discussions are largely manual, placing additional work and stress on presenters and are not feasible for all online meetings, as they rely on human moderators to recognize and address emotional or disruptive statements, which can be difficult to detect in audio-only environments.
Innovation Solution
A method that receives an audio stream, transcribes it in real-time, determines the sentiment of the conversation, and performs corresponding actions based on the sentiment analysis, such as notifying participants or moderators, to provide dynamic feedback and maintain discussion quality.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If human moderators are used to maintain order in online discussions, then discussion quality can be maintained through direct human judgment, but the workload and stress on presenters increases significantly
Solution Approach 1:
The patent introduces an automated sentiment analysis system as an intermediary between participants and moderators. This system processes audio streams, transcribes speech, analyzes sentiment in real-time, and notifies moderators of problematic statements, thereby reducing the direct workload on presenters while maintaining discussion quality through automated monitoring
Solution Approach 2:
The system implements real-time feedback by continuously monitoring conversation sentiment and immediately notifying moderators when disruptive or emotional statements are detected. This feedback loop enables timely intervention while reducing the need for constant human monitoring, thus lowering presenter stress
2Reliability
If human moderators are deployed to detect emotional or disruptive statements, then discussion conduct can be enforced, but this solution is not feasible for all online meetings due to resource constraints
Solution Approach 1:
The system enables discussions to self-monitor through automated sentiment analysis. The audio stream is automatically transcribed and analyzed for emotional or disruptive content without requiring human moderators to be present, making the solution scalable to any online meeting regardless of resource availability
Solution Approach 2:
An automated analysis system serves as an intermediary that can be deployed in any online meeting environment, providing behavior enforcement capabilities without requiring dedicated human moderators, thus increasing adaptability across different meeting types and scales
3Loss of time
If real-time sentiment analysis is performed on audio streams, then disruptive statements can be identified promptly, but the processing complexity and computational resources increase
Solution Approach 1:
The system segments the audio stream into discrete portions for transcription and sentiment analysis. By processing audio in segments rather than as a continuous stream, the computational complexity is managed more effectively while maintaining real-time detection capabilities through systematic breakdown of the processing task
Solution Approach 2:
The patent replaces manual human monitoring with automated computational systems for transcription and sentiment analysis. This substitution handles the processing complexity through algorithmic approaches, enabling real-time analysis without proportional increases in human resources or manual processing burden
Data Source
AI summary
One embodiment provides a method, including: receiving, at an information handling device, a portion of an audio stream associated with a conversation; transcribing, subsequent to the receiving, the portion; determining, by analyzing the transcribed portion, a sentiment associated with the transcribed portion; and performing, responsive to the determining, a function based on the determined sentiment. Other aspects are described and claimed.