Echo Reference Prioritization for Multi-Device Acoustic Echo Control
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Solution Overview
Problem
Existing audio devices struggle with acoustic echo management, particularly in multi-device environments where echo cancellation and suppression are inefficient and resource-intensive, leading to suboptimal performance and increased computational and network costs.
Innovation Solution
Implementing a control system that determines echo reference metrics for multiple audio devices, prioritizes echo references based on importance estimation, and selectively provides these references to echo management systems to optimize echo cancellation and suppression, considering factors like network bandwidth, computational requirements, and ambient noise.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If echo management systems process all audio devices in multi-device environments, then echo cancellation and suppression performance improves, but computational cost and network resource consumption increase
Solution Approach 1:
The system segments the set of all audio devices into two categories: target audio devices (where echo management is actively performed) and non-target audio devices (where echo management is skipped). This segmentation allows the system to maintain high echo cancellation performance for critical devices while reducing overall computational burden by excluding less critical devices from processing.
Solution Approach 2:
The system applies different echo management strategies to different audio devices based on their characteristics and importance. By identifying target audio devices that require intensive echo management and applying standard processing only to non-target devices, the system achieves local optimization of computational resources, improving overall efficiency while maintaining necessary performance levels.
2Reliability
If echo management systems process all audio devices in multi-device environments, then echo cancellation and suppression performance improves, but network resource consumption increases
Solution Approach 1:
The system segments audio devices into target and non-target categories, selectively transmitting echo reference information only for target devices across the network. This segmentation reduces the volume of data transmitted over the network while maintaining effective echo suppression performance for the critical devices that require it most.
Solution Approach 2:
The system extracts and transmits only the essential echo reference information for target audio devices, omitting unnecessary data for non-target devices. This extraction approach minimizes network bandwidth consumption while preserving the critical information needed for effective echo suppression in the most important audio devices.
3Reliability
If echo management systems use more computational resources, then echo cancellation and suppression performance improves, but processing time and system complexity increase
Solution Approach 1:
The system dynamically adjusts its complexity by adaptively identifying which audio devices qualify as target devices based on real-time conditions and device characteristics. This dynamic approach allows the system to simplify processing for non-target devices while maintaining comprehensive echo mitigation for target devices, optimizing the balance between performance and complexity.
Solution Approach 2:
By segmenting the audio device population into target and non-target groups, the system reduces overall complexity by applying simplified or no echo management to non-target devices while concentrating computational resources on target devices. This segmentation strategy maintains necessary echo mitigation performance while significantly reducing system-wide complexity.
Data Source
AI summary
Some implementations involve receiving location information for each of a plurality of audio devices in an audio environment, generating, based at least in part on the location information, rendering information for a plurality of audio devices in an audio environment and determining, based at least on part on the rendering information, a plurality of echo reference metrics. Each echo reference metric may correspond to audio data reproduced by one or more audio devices of the plurality of audio devices. The rendering information may include a matrix of loudspeaker activations. Some examples involve making, based at least in part on the echo reference metrics, an importance estimation for each of a plurality of echo references, selecting, based at least in part on the importance estimation, one or more echo references and providing them to at least one echo management system for canceling or suppressing echoes.