Audio Visualization Engine for Virtual Meeting Noise Detection
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Solution Overview
Problem
Users participating in virtual online meetings may not be aware of audio issues, such as background noise, affecting the quality of their audio data, as they cannot perceive these problems visually.
Innovation Solution
A Visualization Engine that detects specific audio events, like background noise, and generates visualizations within the virtual meeting environment, providing users with visual cues about the quality of their audio, using machine learning models to render these visualizations based on detected attributes.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Loss of information
If audio data is transmitted without visual feedback, then bandwidth and processing resources are conserved, but users cannot perceive audio quality issues
Solution Approach 1:
The patent introduces an audio visualization intermediary component that converts audio data into visual representations. This mediator processes audio streams and generates corresponding visual feedback, allowing users to perceive audio quality issues without adding significant complexity to the core audio transmission system. The visualization acts as a bridge between audio data and user perception.
Solution Approach 2:
The patent replaces the mechanical/acoustic perception channel with an optical/visual channel for audio quality feedback. Instead of relying on users to hear audio issues directly, the system substitutes audio perception with visual representation, enabling users to see audio quality problems through generated visualizations.
2Reliability
If real-time audio visualization is implemented, then users can detect audio issues immediately, but computational resources and processing time increase
Solution Approach 1:
The patent implements partial action by selectively visualizing only certain audio quality metrics or specific time windows of audio data rather than processing and visualizing all audio data continuously. This approach provides sufficient audio quality detection while reducing the computational burden on the system.
Solution Approach 2:
The audio visualization system performs self-service by automatically analyzing audio streams and generating visual feedback without requiring external intervention or complex processing infrastructure. The system uses readily available audio data and applies efficient algorithms to create visualizations independently.
3Measurement precision
If detailed audio event detection is performed, then audio quality feedback precision is improved, but system complexity and processing overhead increase
Solution Approach 1:
The patent segments audio event detection into distinct, modular components that identify specific audio characteristics separately. By dividing the detection process into discrete segments (e.g., noise detection, echo detection, volume level detection), the system achieves precise audio quality feedback while maintaining manageable complexity through modular architecture.
Data Source
AI summary
Various embodiments of an apparatus, method(s), system(s) and computer program product(s) described herein are directed to a Visualization Engine. The Visualization Engine receives audio data associated with a user account accessing a virtual meeting via a communications environment client software application. The Visualization Engine detects presence of a pre-selected type(s) of audio event(s) in the received audio data. The Visualization Engine generates a visualization representative of at least one attribute of the detected audio event(s). During playback of the audio data in the virtual meeting, the Visualization Engine renders the visualization within the communications environment client software application of the user account.