Audio Processing Optimization in Multi-Participant Conference
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Solution Overview
Problem
Existing network solutions typically use a single topology for establishing communication between computing devices, which leads to advantages in certain aspects but also results in disadvantages, such as inefficient resource utilization and processing costs, especially in handling multiple media types like audio data in conferencing scenarios.
Innovation Solution
The use of dual network topologies, specifically a mesh network for game data and a focus point star network for audio data, where the focus point network dynamically designates a hub to optimize audio processing by bypassing unnecessary operations for silent participants and reducing computational resources.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If a single network topology is used to relay all media content, then network simplicity is maintained, but processing efficiency and resource utilization deteriorate
Solution Approach 1:
The patent segments the network into two distinct topologies: a mesh network for relaying game data and a star network for relaying audio data. This segmentation allows each network type to be optimized for its specific media content, improving processing efficiency while managing complexity through functional separation.
Solution Approach 2:
The patent implements a multi-functional network system where computing devices can participate in both the mesh network (for game data) and the star network (for audio data). This universality allows the system to handle multiple media types simultaneously, improving overall productivity without requiring completely separate systems.
2Ease of operation
If a focus point network is used to relay audio data, then audio processing is centralized and simplified, but computational resource consumption increases at the focus point
Solution Approach 1:
The patent implements dynamic focus point designation where the focus point computing device is selected based on current network conditions and participant activity. This dynamic selection optimizes computational resource consumption by assigning the heavy lifting to the most suitable device at any given time, while maintaining the simplicity of centralized audio processing through the star network topology.
Solution Approach 2:
The network system automatically manages focus point designation and audio routing without requiring manual intervention. The system self-organizes to select appropriate focus points and route audio data efficiently, reducing the operational burden while optimizing resource utilization across the network.
3Reliability
If all participants are processed equally in the audio stream, then processing consistency is maintained, but computational resources are wasted on silent participants
Solution Approach 1:
The patent applies local quality by differentiating processing based on participant characteristics. Instead of uniform processing, the system identifies silent participants and applies different handling (bypassing or reducing processing) compared to active participants. This maintains processing consistency for active users while reducing energy consumption for silent users.
Solution Approach 2:
The patent implements partial action by selectively processing only the audio streams of active participants rather than all participants uniformly. Silent participants have their audio processing reduced or bypassed entirely, which reduces computational resource waste while maintaining adequate processing for those who need it most.
4Adaptability or versatility
If dynamic focus point re-designation is implemented, then network adaptability improves, but system complexity and potential interruptions increase
Solution Approach 1:
The patent implements dynamic focus point re-designation to adapt to changing network conditions and participant availability. This dynamic approach improves network adaptability by selecting optimal focus points in real-time, while the system manages session continuity through structured re-designation protocols that minimize disruptions during transitions.
Data Source
AI summary
A first computing device distributes audio streams to several computing devices of participants in a communication session. Some embodiments establishes a star network with the first computing device as a central network hub for receiving audio streams from other computing devices, compositing the audio streams and distributing the composited audio streams to the other computing devices. Through the star network, the first computing device receives audio streams from the other computing devices. The first computing device generates at least two different composite audio streams for at least two different computing devices by (i) identifying a set of silent participants in the communication session, and (ii) eliminating redundant audio processing operations that produce the same composite audio streams for different computing devices because of the identified set of silent participants. The first computing device sends each computing device the composited audio stream for the device.