声源定位的局部相对传递函数

Xiaofei Li, R. Horaud, Laurent Girin, S. Gannot
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引用次数: 11

摘要

相对传递函数(RTF),即两个传感器之间的声学传递函数之比,可用于基于麦克风阵列的声源定位/波束形成。RTF通常是根据唯一的参考传感器来定义的。选择参考传感器可能是一项困难的任务,特别是对于动态声学环境和设置。在本文中,我们建议使用局部归一化RTF(简称local-RTF)作为声学特征来表征声源方向。Local-RTF将邻居传感器作为给定传感器的参考通道。因此,估计的局部RTF向量可以避免噪声唯一参考的不良影响,并且具有比传统RTF估计器更小的估计误差。我们提出了两个局部rtf估计量,并将传感器和频率之间的值连接起来形成一个高维向量,用于源定位。对真实世界信号的实验显示了这种方法的有趣之处。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Local relative transfer function for sound source localization
The relative transfer function (RTF), i.e. the ratio of acoustic transfer functions between two sensors, can be used for sound' source localization / beamforming based on a microphone array. The RTF is usually defined with respect to a unique reference sensor. Choosing the reference sensor may be a difficult task, especially for dynamic acoustic environment and setup. In this paper we propose to use a locally normalized RTF, in short local-RTF, as an acoustic feature to characterize the source direction. Local-RTF takes a neighbor sensor as the reference channel for a given sensor. The estimated local-RTF vector can thus avoid the bad effects of a noisy unique reference and have smaller estimation error than conventional RTF estimators. We propose two estimators for the local-RTF and concatenate the values across sensors and frequencies to form a high-dimensional vector which is utilized for source localization. Experiments with real-world signals show the interest of this approach.
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