Particle filtering algorithms for tracking an acoustic source in a reverberant environment

D. Ward, E. Lehmann, R. C. Williamson
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引用次数: 358

Abstract

Traditional acoustic source localization algorithms attempt to find the current location of the acoustic source using data collected at an array of sensors at the current time only. In the presence of strong multipath, these traditional algorithms often erroneously locate a multipath reflection rather than the true source location. A recently proposed approach that appears promising in overcoming this drawback of traditional algorithms, is a state-space approach using particle filtering. In this paper we formulate a general framework for tracking an acoustic source using particle filters. We discuss four specific algorithms that fit within this framework, and demonstrate their performance using both simulated reverberant data and data recorded in a moderately reverberant office room (with a measured reverberation time of 0.39 s). The results indicate that the proposed family of algorithms are able to accurately track a moving source in a moderately reverberant room.
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在混响环境中跟踪声源的粒子滤波算法
传统的声源定位算法试图仅使用在当前时间从传感器阵列收集的数据来找到声源的当前位置。在强多径存在的情况下,这些传统算法往往会错误地定位多径反射而不是真实的源位置。最近提出的一种方法似乎有望克服传统算法的这一缺点,即使用粒子滤波的状态空间方法。在本文中,我们制定了一个使用粒子滤波器跟踪声源的一般框架。我们讨论了适合该框架的四种特定算法,并使用模拟混响数据和在中等混响办公室(测量混响时间为0.39秒)中记录的数据演示了它们的性能。结果表明,所提出的算法家族能够准确地跟踪中等混响房间中的移动源。
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Errata to "Using Steady-State Suppression to Improve Speech Intelligibility in Reverberant Environments for Elderly Listeners" Farewell Editorial Inaugural Editorial: Riding the Tidal Wave of Human-Centric Information Processing - Innovate, Outreach, Collaborate, Connect, Expand, and Win Three-Dimensional Sound Field Reproduction Using Multiple Circular Loudspeaker Arrays Introduction to the Special Issue on Processing Reverberant Speech: Methodologies and Applications
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