Beamforming Microphone Array Noise Field Mapping
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Solution Overview
Problem
Conferencing environments face challenges in effectively capturing sound due to ambient background noise, which masks speech intelligibility and is exacerbated by the complexity of configuring microphone arrays to account for changing noise sources and environments.
Innovation Solution
A system that uses a beamforming microphone array to determine a noise field map by measuring ambient noise levels across a room, independent of noise source location, and modifies the operation of audio devices based on this map to reduce unwanted noise through digital signal processing techniques.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Device complexity
If traditional microphones with fixed polar patterns are used to capture sound in conferencing environments, then the device complexity is low, but speech intelligibility deteriorates due to capturing unwanted ambient background noise
Solution Approach 1:
The system segments the audio capture function by using multiple microphone elements arranged in an array, where each element captures sound from a specific spatial direction. This segmentation enables the system to distinguish between desired speech sources and unwanted ambient noise based on their spatial characteristics, resolving the contradiction between simple device configuration and effective noise rejection.
Solution Approach 2:
The system implements dynamic beamforming where the pickup pattern can be electronically steered and adapted in real-time based on the spatial distribution of sound sources. This dynamic capability allows the microphone array to focus on desired speech while suppressing ambient noise from other directions, improving speech intelligibility without requiring complex manual configuration.
2Object-affected harmful factors
If microphone array systems are configured to provide steerable coverage patterns, then speech capture capability is improved, but the initial and ongoing configuration becomes complex and time-consuming
Solution Approach 1:
The system performs self-configuration by automatically detecting the spatial distribution of sound sources and adapting its beamforming patterns accordingly. The noise field mapping process enables the system to autonomously identify areas of elevated noise and adjust its pickup patterns without requiring manual intervention, thereby improving speech capture while eliminating configuration complexity.
Solution Approach 2:
The system uses feedback from the noise field map to continuously optimize its beamforming configuration. By monitoring the spatial noise distribution and adjusting the pickup patterns in response, the system maintains optimal speech capture capability while automatically adapting to changing environmental conditions without complex manual reconfiguration.
3Productivity
If microphone arrays are initially configured to capture sound from specific areas, then coverage is optimized for those areas, but the system cannot adapt when noise sources or audio sources move to new locations
Solution Approach 1:
The system implements dynamic adaptation by continuously updating the noise field map and adjusting beamforming patterns in real-time. This allows the system to maintain optimal coverage and noise rejection even when noise sources or speech sources move to new locations, resolving the contradiction between initial coverage optimization and ongoing environmental adaptability.
Solution Approach 2:
The system performs preliminary noise field mapping to establish a baseline understanding of the acoustic environment before optimization. This preliminary action enables the system to proactively adapt to noise sources and speech sources as they move, maintaining coverage optimization without requiring reactive reconfiguration.
4Object-affected harmful factors
If digital signal processing techniques are applied to reduce ambient noise, then speech intelligibility is improved, but processing time and computational resources increase
Solution Approach 1:
The system extracts spatial information from the noise field map to identify and target specific areas of elevated noise for processing. By focusing computational resources only on relevant spatial regions rather than processing all audio data uniformly, the system improves speech intelligibility while minimizing processing time and computational overhead.
Applied Scientific Principles
This section explains which scientific principles are used to turn an abstract innovation direction into a practical engineering solution.
Function Achieved in This Case
Enhances speech intelligibility by identifying and treating areas of elevated noise, improving the overall audio experience in conferencing environments by reducing background noise and maintaining optimal sound capture.
Implementation Method 1
a beamforming microphone array to determine a noise field map by measuring ambient noise levels across a room
Data Source
AI summary
Systems and methods configured to employ a beamforming microphone array to determine a noise field map of a conferencing environment and modify operation of the beamforming microphone array responsive to the determined noise field map.