3D Localization of Multiple Simultaneous Speakers with Discrete Wavelet Transform and Proposed 3D Nested Microphone Array

A. D. Firoozabadi, H. Durney, I. Soto, Miguel Sanhueza-Olave
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Abstract

Multiple sound source localization is one of the important topic in speech processing. GCC function is used as a traditional algorithm for sound source localization. This function estimates DOA for multiple speakers by calculation the cross-correlation between microphone signals but its accuracy decreases in adverse conditions. The aim of proposed method in this paper is localization of multiple simultaneous speakers in undesirable condition. The proposed method is based on novel 3D nested microphone array in combination with obtained information of Discrete Wavelet Transform (DWT) and subband processing. The proposed 3D nested microphone array prepares the condition for 3D localization and eliminates the spatial aliasing between microphone signals. Also, we propose the DWT for extraction the information of speech signal. Since, the spectral information of speech signal concentrates on low frequencies, we propose a structure of filter bank based on DWT to increase the frequency resolution on low frequencies. The performed evaluation on real and simulated data shows the superiority of our proposed method in comparison with Fullband and subband processing with uniform filters and uniform microphone array.
基于离散小波变换的多个同步扬声器三维定位及三维嵌套麦克风阵列
多声源定位是语音处理中的一个重要课题。传统的声源定位算法采用GCC函数。该函数通过计算麦克风信号之间的相互关系来估计多个扬声器的DOA,但在不利条件下其精度会降低。本文提出的方法的目的是在不理想的情况下对多个同时说话人进行定位。该方法基于一种新型的三维嵌套式麦克风阵列,并结合离散小波变换(DWT)和子带处理得到的信息。所提出的三维嵌套式麦克风阵列为三维定位准备了条件,并消除了麦克风信号之间的空间混叠。此外,我们还提出了一种用于提取语音信号信息的小波变换方法。针对语音信号频谱信息集中在低频的特点,提出了一种基于小波变换的滤波器组结构,以提高低频的频率分辨率。通过对真实数据和仿真数据的分析,对比均匀滤波器和均匀传声器阵列的全带和子带处理,表明了该方法的优越性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
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