近距离双麦克风对多运动声源方向的估计

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清华大学辅仁网/2017-07-07

近距离双麦克风对多运动声源方向的估计

宫琴^1,2, 刘毅¹

1. 清华大学生物医学工程系, 北京 100084;
2. 清华大学深圳研究生院, 生物医学研究中心, 深圳 518055

Estimation for the location of multiple moving sound sources in small-distance dual-microphone

GONG Qin^1,2, LIU Yi¹

1. Department of Biomedical Engineering, Tsinghua University, Beijing 100084, China;
2. Research Center of Biomedical Engineering, Graduate School at Shenzhen, Tsinghua University, Shenzhen 518055, China

摘要:

输出: BibTeX | EndNote (RIS)

摘要在基于双麦克风的声学场景分析中，当双麦克风间距变小并且多个声源不断运动时，传统方法对于多个运动声源角度估计的准确性会降低。该文提出了一种适用于近距离双麦克风，对多个运动声源方向进行估计的方法。该方法提出利用改进的Gammatone滤波器对混合声源样本进行时频分析，通过提取与声源方向相对应的过零点时间差（zero-crossing time difference，ZCTD）的特征信息，利用Gauss函数对ZCTD进行统计分析，最终实现多个运动声源方向的确定。对于不同性质、不同速度、不同轨迹的多个运动声源，测试结果表明：该方法对其角度的估计准确性较好。

关键词 ：信号声学,双麦克风,运动声源,Gammatone滤波器,过零点时间差(ZCTD),Gauss函数

Abstract：Angle measurements using traditional auditory analyse with dual-microphones have limited accuracy when the two microphones are close together and the sound sources are moving. This paper presents a method for multiple moving sound source localization with two closely spaced microphones. The method uses an improved gammatone filter bank for the time-frequency analysis of the mixed sound samples, extracts the zero-crossing time difference (ZCTD) that reflects the sound source location feature information and finally statistically analyzes the ZCTD with a Gaussian function to localize the sound source. Tests show that this method gives accurate angle estimates for various kinds of sound sources with various moving speeds along various trajection.

Key words：signal acoustics dual-microphone moving sound source gammatone filter bank zero-crossing time difference Gauss's function

收稿日期: 2016-04-11 出版日期: 2016-08-23

ZTFLH:

TN912.16

引用本文:

宫琴, 刘毅. 近距离双麦克风对多运动声源方向的估计[J]. 清华大学学报（自然科学版）, 2016, 56(8): 901-907.
GONG Qin, LIU Yi. Estimation for the location of multiple moving sound sources in small-distance dual-microphone. Journal of Tsinghua University(Science and Technology), 2016, 56(8): 901-907.

链接本文:

http://jst.tsinghuajournals.com/CN/10.16511/j.cnki.qhdxxb.2016.25.032或 http://jst.tsinghuajournals.com/CN/Y2016/V56/I8/901

图表:

图1 算法基本流程

表1 3段语音的语义

图2 多个静止声源角度的估计结果

表2 多个静止声源角度的估计结果

图3 多个运动声源角度的估计结果

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