Steerable Microphone Array for Continuous Acoustic Source Tracking

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Solution Overview

Problem

Conventional microphone systems struggle to capture and output audio signals effectively when acoustic sources navigate or change positions within an acoustic environment, especially in the presence of multiple sources and noise, leading to poor quality processing.

Innovation Solution

Employing steerable microphone arrays with beamforming and localization techniques, combined with machine learning models, to identify and continuously track acoustic sources, ensuring improved capture and output of audio signals.

Engineering Contradictions & Design Principles

VSEngineering Contradiction Analysis

1Manufacturing precision

If conventional microphone systems are used to capture audio signals from moving acoustic sources, then the system structure is simple, but the audio signal capture quality deteriorates when sources change position

Engineering Contradiction:
Improveaudio signal capture qualityVSAvoidmicrophone system structure
Core Design Contradiction:
Manufacturing precisionVSDevice complexity

Solution Approach 1:

The patent implements dynamic beamforming where the microphone array continuously adjusts its sensitivity patterns in real-time to track moving acoustic sources. The system uses adaptive algorithms that modify the beamforming weights based on source position, allowing the microphone system to dynamically follow speakers as they move through the environment, thereby maintaining high capture quality without requiring physical repositioning of microphones

Inventive Principle:
Principle #15Dynamics

Solution Approach 2:

The patent creates a multi-functional audio system that simultaneously performs source localization, tracking, and audio capture. The same microphone array used for capturing audio signals also serves to detect source positions and guide beamforming adjustments, eliminating the need for separate tracking devices and reducing overall system complexity while improving capture quality

Inventive Principle:
Principle #6Universality (Multi-functionality)

2Manufacturing precision

If audio capture devices attempt to follow moving acoustic sources, then the audio signal capture quality improves, but the system cannot effectively handle multiple simultaneous sources

Engineering Contradiction:
Improveaudio signal capture qualityVSAvoidhandling multiple acoustic sources
Core Design Contradiction:
Manufacturing precisionVSAdaptability or versatility

Solution Approach 1:

The patent segments the acoustic environment by creating distinct beamforming lobes for each detected acoustic source. The system divides the spatial spectrum into multiple directional beams, each targeted at a specific source position. This allows the microphone array to simultaneously capture audio from multiple speakers by allocating separate beamforming resources to each source, preventing interference and maintaining quality for all sources

Inventive Principle:
Principle #1Segmentation

Solution Approach 2:

The patent dynamically changes beamforming parameters such as lobe direction, width, and gain based on the positions and characteristics of multiple acoustic sources. The system adjusts these parameters in real-time to optimize capture quality for each source while managing the overall acoustic environment, enabling effective handling of multiple simultaneous speakers through continuous parameter optimization

Inventive Principle:
Principle #35Parameter changes

Data Source

PatentUS20250113143A1Identification and continuous tracking of an acoustic source
Publication Date: 2025.04.03 SHURE ACQUISITION HLDG INC
  • US20250113143A1 patent drawing
  • US20250113143A1 patent drawing
  • US20250113143A1 patent drawing

AI summary

Embodiments disclosed herein are configured to provide automatic identification and continuous tracking of an acoustic source generating audio signals in an acoustic environment. Embodiments can receive audio signals captured by steerable microphone arrays situated within the acoustic environment and identify, based on the audio signals and an acoustic source identification model, the acoustic source associated with the audio signals. Embodiments can generate, based on the audio signals, a localization object associated with the acoustic source and direct, based on the localization object, microphone lobes associated with the steerable microphone arrays toward the acoustic source. Embodiments can also generate, based on receiving subsequent audio signals, an updated localization object associated with the acoustic source and direct, based on the updated localization object, the microphone lobes of the steerable microphone arrays toward the acoustic source.