摘要
在噪声和混响的声学环境中,基于双耳时间差的声源方位角定位性能会严重降低;针对这个问题,提出了一种基于子带选择和DBSCAN的双耳声源定位算法,首先,采用Gammatone滤波器将双耳声源信号分解为若干个子带信号;其次,根据子带能量大小进行子带通道数压缩;然后,根据子带信噪比大小获取最优子带,降低无关子带干扰;接着将子带信号进行分帧,根据互相关算法获取峰值处的数据点;最后,引入DBSCAN算法消除噪声点的影响,获取最优数据点,从而根据ITD定位模型判断目标声源方位角,实验结果表明,该算法在复杂的声学环境中,相较于传统的互相关算法,可显著提高双耳声源方位角定位性能。
In noisy and reverberant acoustic environments,the performance of sound source azimuth angle localization based on binaural time difference is severely degraded.To solve this problem,a binaural sound source angle localization algorithm based on the subband selection and density-based spatial clustering of applications with noise(DBSCAN)is proposed.Firstly,the binaural sound source signal is decomposed into several subband signals by using the Gammatone filter;Secondly,the number of the subband channels is compressed according to the subband energy;Then,the optimal subband is obtained according to signal to noise ratio of the subband,the interference of irrelevant subbamds is reduced,the subband signal is divided into frames,and the data points at the peak are obtained according to the cross-correlation algorithm;Finally,the DBSCAN algorithm is introduced to eliminate the influence of noise points and obtain the optimal data points,so the target sound source azimuth angle localization is determined according to the interaural time difference(ITD)positioning model.The experimental results show that,compared with the traditional cross-correlation algorithm in complex acoustic environments,the algorithm can significantly improve the azimuth angle localization performance of the binaural sound sources.
作者
陈国良
赵祥瑞
CHEN Guoliang;ZHAO Xiangrui(School of Mechanical and Electronic Engineering,Wuhan University of Technology,Wuhan 430070,China)
出处
《计算机测量与控制》
2022年第11期204-212,共9页
Computer Measurement &Control
关键词
双耳声源定位
数据压缩
子带选择
互相关算法
DBSCAN
binaural sound source localization
data compression
subband selection
cross-correlation algorithm
DBSCAN