Auto-Mute Audio Processing for Online Meeting Noise
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Solution Overview
Problem
During online meetings, unpredictable and uncontrollable environments often lead to interruptions such as background noise, disrupting communications and requiring manual intervention for muting and unmuting, which can impact other attendees.
Innovation Solution
A computer-implemented method using processor-based audio signal processing to compare incoming audio data with known voice and interruption datasets, automatically muting or unmuting a user's audio connection based on the presence of voice or noise signals, employing speaker recognition and auto-mute/unmute components to manage interruptions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If manual mute/unmute intervention is used to handle noise during online meetings, then the speaker can resolve the noise problem, but the communication is interrupted and other attendees are impacted before mute is activated
Solution Approach 1:
The system performs preliminary detection of noise and automatically mutes the audio connection before the noise can significantly impact the meeting. By detecting interruption signals and voice signals in advance and taking automated action, the system eliminates the delay associated with manual intervention while maintaining reliable noise handling.
Solution Approach 2:
The system enables self-service by automatically detecting noise conditions and muting/unmuting the audio connection without requiring manual intervention from the speaker or meeting host. The automated audio signal processing system monitors the audio stream, identifies interruption signals, and autonomously manages the mute state to maintain meeting quality.
2Productivity
If automatic audio signal processing is implemented to detect and differentiate voice signals from noise, then communication continuity is improved, but device complexity increases
Solution Approach 1:
The patent replaces manual mechanical intervention (clicking mute buttons) with automated electronic audio signal processing. The system uses digital signal processing to analyze audio streams, differentiate between voice signals and interruption signals, and automatically control the audio connection state, thereby maintaining communication continuity without manual device operation.
Solution Approach 2:
The system introduces an intermediary audio signal processing component that acts as a mediator between the microphone input and the audio output to other meeting participants. This intermediary analyzes the audio stream in real-time, identifies noise conditions, and selectively blocks or passes audio signals, enabling intelligent noise filtering without requiring complex user-side modifications.
3Reliability
If the audio connection is automatically muted upon detecting noise, then meeting quality is maintained, but false muting of valid speaker audio may occur
Solution Approach 1:
The system applies local quality by differentiating between different types of audio signals at the source level. Instead of applying a uniform mute action to all audio, the system analyzes the characteristics of each audio segment and applies selective muting only to identified interruption signals while preserving valid voice signals. This localized approach ensures meeting quality is maintained without false muting of legitimate speaker audio.
Data Source
AI summary
A method, a system, and a computer program product for managing interruptions during a network based conference. An audio data stream received from at least one user device communicatively coupled to a network-based conference is received. The processed audio data stream is compared to at least one known voice signal dataset and at least one known interruption signal dataset. An audio connection of the user device to the network-based conference is muted while the user device is communicatively coupled to the network-based conference, based on a determination that the processed audio data stream includes at least one audio signal corresponding to at least one audio signal in the known interruption signal dataset.