一个圆形的麦克风阵列与基于声学信息的神经网络的虚拟麦克风
Sipei Zhao1, Fei Ma1
1Centre for Audio, Acoustics and Vibration, Faculty of Engineering and IT, University of Technology Sydney, Sydney, Australia.
The Journal of the Acoustical Society of America
|July 15, 2024
概括
这项研究引入了虚拟麦克风,以增强圆形麦克风阵列光束形成,克服特定频率的性能下降. 这种新的方法可以改善声信号的聚焦,而无需进行物理阵列修改.
科学领域:
- 声学 声学 在声学方面
- 信号处理 信号处理
- 机器学习 机器学习
背景情况:
- 声波束成形使用麦克风阵列来聚焦声音并减少干扰.
- 圆形麦克风阵列因贝塞尔函数零而面临特定频率的性能问题.
- 现有的解决方案,如混或同心数组,具有实际的缺点 (体积,复杂性,成本).
研究的目的:
- 提出一种新的方法来改进使用圆形麦克风阵列的声波束成形.
- 为了解决性能退化问题而没有物理阵列修改.
- 为了提高光束成形在现实世界的场景中的准确性和适用性.
主要方法:
- 用虚拟麦克风增强圆形麦克风阵列的实现.
- 使用声学信息的神经网络来预测虚拟麦克风位置的声音压力.
- 整合物理和虚拟麦克风压力数据用于光束变频器设计.
主要成果:
- 成功消除了与关键频率的圆形数组相关的性能降低.
- 在更高的频率下,已被证明可以抑制空间别名.
- 通过实验结果验证了虚拟麦克风方法的有效性.
结论:
- 拟议的虚拟麦克风技术有效地克服了传统圆形麦克风阵列的局限性.
- 这种方法为提高声波束成形性能提供了一个实用的解决方案.
- 该方法显示了高级音频信号处理应用的巨大潜力.
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