声源定位的转向响应功率:教程回顾

Eric Grinstein, Elisa Tengan, Bilgesu Çakmak, Thomas Dietzen, Leonardo Nunes, Toon van Waterschoot, Mike Brookes, Patrick A. Naylor
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引用次数: 0

摘要

在过去的三十年里,转向响应功率(SRP)方法因其在中等混响和嘈杂环境下令人满意的定位性能,被广泛用于声源定位(SSL)任务。许多作品对原始 SRP 方法进行了分析和扩展,以降低其计算成本,使其能够定位多个声源,或提高其在不利环境中的性能。在这项工作中,我们回顾了有关 SRP 方法及其变体的 200 多篇论文,重点是 SRP-PHAT 方法。我们还介绍了 eXtensible-SRP,或称 X-SRP,它是 SRP 算法的一个通用模块化版本,可以实现所回顾的扩展。我们提供了该算法的 Python 实现,其中包括从文献中选取的扩展。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
Steered Response Power for Sound Source Localization: A Tutorial Review
In the last three decades, the Steered Response Power (SRP) method has been widely used for the task of Sound Source Localization (SSL), due to its satisfactory localization performance on moderately reverberant and noisy scenarios. Many works have analyzed and extended the original SRP method to reduce its computational cost, to allow it to locate multiple sources, or to improve its performance in adverse environments. In this work, we review over 200 papers on the SRP method and its variants, with emphasis on the SRP-PHAT method. We also present eXtensible-SRP, or X-SRP, a generalized and modularized version of the SRP algorithm which allows the reviewed extensions to be implemented. We provide a Python implementation of the algorithm which includes selected extensions from the literature.
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