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Multiple Sound Sources Localization with Frame-by-Frame Component Removal of Statistically Dominant Source

机译:多种声音源本地化与逐帧组件删除统计主导源

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摘要

Multiple sound sources localization is a hot topic in audio signal processing and is widely utilized in many application areas. This paper proposed a multiple sound sources localization method based on a statistically dominant source component removal (SDSCR) algorithm by soundfield microphone. The existence of the statistically weak source (SWS) among soundfield microphone signals is validated by statistical analysis. The SDSCR algorithm with joint an intra-frame and inter-frame statistically dominant source (SDS) discriminations is designed to remove the component of SDS while reserve the SWS component. The degradation of localization accuracy caused by the existence of the SWS is resolved using the SDSCR algorithm. The objective evaluation of the proposed method is conducted in simulated and real environments. The results show that the proposed method achieves a better performance compared with the conventional SSZ-based method both in sources localization and counting.
机译:多个声源定位是音频信号处理中的热门话题,并且广泛用于许多应用领域。本文提出了一种基于Soundfield麦克风的统计主导源分量移除(SDSCR)算法的多声源定位方法。通过统计分析验证声场麦克风信号中统计上弱源(SWS)的存在。具有帧内帧内和帧内统计主导源(SDS)鉴别的SDSCR算法旨在拆除SWS组件的同时卸下SDS的组件。使用SDSCR算法解析由SWS存在引起的本地化精度的劣化。所提出的方法的客观评估在模拟和真实环境中进行。结果表明,与源本地化和计数的传统基于SSZ的方法相比,该方法实现了更好的性能。

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