Distributed Call-State Audio Muting for Interference Reduction
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Solution Overview
Problem
It is increasingly difficult to conduct or participate in a call without being interrupted by intruding noise from other audio sources, leading to embarrassing and unwelcome interruptions during work calls or online meetings.
Innovation Solution
A computing device enters a high priority call state and transmits a message via a distributed context network to other devices to reduce their audio output volume, using threshold levels and calibration operations to minimize interference.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If audio output volume is increased to ensure clear audio transmission, then audio quality is improved, but audio interference to other calls increases
Solution Approach 1:
The system dynamically adjusts audio output volume based on the operational state of computing devices. When a device detects that another device is in a high-priority call state, it automatically reduces its audio output volume to minimize interference, while maintaining normal volume during other operations. This dynamic adjustment resolves the contradiction by adapting audio quality to contextual requirements.
Solution Approach 2:
The system implements feedback mechanisms where computing devices monitor the operational states of nearby devices and adjust audio output accordingly. When a device detects that another device is actively engaged in a high-priority call, it receives feedback information and reduces its audio volume to prevent interference, thereby maintaining audio quality without disrupting ongoing calls.
2Object-affected harmful factors
If audio output volume is reduced to minimize interference, then audio interference is decreased, but audio quality deteriorates
Solution Approach 1:
The system dynamically adjusts audio output volume based on the operational state of computing devices. When a device detects that another device is in a high-priority call state, it automatically reduces its audio output volume to minimize interference, while maintaining normal volume during other operations. This dynamic adjustment resolves the contradiction by adapting audio quality to contextual requirements.
Solution Approach 2:
The system changes the audio output parameter (volume) based on detected conditions. When interference is detected or predicted through calibration operations and state monitoring, the system modifies the audio parameter to a lower volume level. This parameter change allows the system to minimize interference while maintaining acceptable audio quality through contextual adaptation.
3Measurement precision
If calibration operations are performed with all devices, then measurement precision is improved, but device complexity increases
Solution Approach 1:
Instead of requiring calibration operations with all computing devices in the network, the system performs calibration selectively with devices that are detected to be in high-priority call states or are identified as potential interference sources through audio monitoring. This partial action approach maintains sufficient measurement precision for interference management while significantly reducing the overall complexity of calibration operations.
Solution Approach 2:
The system performs self-calibration through automated audio monitoring and state detection. Devices automatically monitor audio output levels and operational states, and the system uses this self-generated data to identify calibration needs and perform targeted calibration operations. This self-service mechanism reduces complexity by eliminating the need for manual calibration procedures across all devices.
Data Source
AI summary
A method of managing audio output of a computing device comprises, receiving via a distributed context network a message indicating that another computing device has entered a high priority call state, and reducing audio output volume of the computing device in response to receiving the message.