The Steered Response Power(SRP)method works well for sound source localization in noisy and reverberant environment.However,the large computation complexity limits its practical application.In this paper,a fast SRP se...The Steered Response Power(SRP)method works well for sound source localization in noisy and reverberant environment.However,the large computation complexity limits its practical application.In this paper,a fast SRP search method is proposed to reduce the computational complexity using small-aperture microphone array.The proposed method inspired by the SRP spatial spectrum includes two steps:first,the proposed method estimates the azimuth of the sound source roughly and determines whether the sound source is in far field or near field;then,different fine searching operations are performed according to the sound source being in far field or near field.Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computation complexity of the proposed method with those of the conventional SRP-PHAT algorithm.The results show that,the proposed method has a comparative accuracy with the conventional SRP algorithm,and achieves a reduction of 93.62%in computation complexity compared to the conventional SRP algorithm.展开更多
针对平面麦克风阵列的声源三维坐标估计问题,文中在TDOA(Time Difference of Arrival)声源定位算法中引入粒子群优化算法进行位置估计。利用PHAT(Phase Transform)加权函数的广义互相关法计算得到时延差的真实值,结合麦克风的坐标位置,...针对平面麦克风阵列的声源三维坐标估计问题,文中在TDOA(Time Difference of Arrival)声源定位算法中引入粒子群优化算法进行位置估计。利用PHAT(Phase Transform)加权函数的广义互相关法计算得到时延差的真实值,结合麦克风的坐标位置,通过几何关系计算出假设声源到达麦克风之间的时延差的估计值。设计时延真实值和估计值差值的平方和为粒子适应度函数,利用粒子群优化算法搜索空间中符合适应度函数的声源点,实现声源位置估计。仿真结果表明,在计算速度与球形插值法相近的情况下,文中所提算法比球形插值法具有更好的鲁棒性和抗噪性。展开更多
The research on finding the arrival directions of speech signals by microphone arrny is proposed. We first analyze the uniform microphone array and give the design for microphone array applied in the hand-free speech ...The research on finding the arrival directions of speech signals by microphone arrny is proposed. We first analyze the uniform microphone array and give the design for microphone array applied in the hand-free speech recognition. Combining the traditional direction finding technique of MUltiple SIgnal Classification (MUSIC) with the focusing matrix method, we improve the resolving power of the microphone array for multiple speech sources.As one application of finding Direction of Arrival (DOA), a new microphone-array system for noise reduction is proposed. The new system is based on maximum likelihood estimate technique which reconstruct superimposed signals from different directions by using DOA information. The DOA information is got in terms of focusing MUSIC method which has been proven to have high performance than conventional MUSIC method on speaker localization[1].展开更多
基金Supported by the National Natural Science Foundation of China(No.61201345)the Beijing Key Laboratory of Advanced Information Science and Network Technology(No.XDXX1308)
文摘The Steered Response Power(SRP)method works well for sound source localization in noisy and reverberant environment.However,the large computation complexity limits its practical application.In this paper,a fast SRP search method is proposed to reduce the computational complexity using small-aperture microphone array.The proposed method inspired by the SRP spatial spectrum includes two steps:first,the proposed method estimates the azimuth of the sound source roughly and determines whether the sound source is in far field or near field;then,different fine searching operations are performed according to the sound source being in far field or near field.Experiments both in simulation environments and real environments have been performed to compare the localization accuracy and computation complexity of the proposed method with those of the conventional SRP-PHAT algorithm.The results show that,the proposed method has a comparative accuracy with the conventional SRP algorithm,and achieves a reduction of 93.62%in computation complexity compared to the conventional SRP algorithm.
文摘针对平面麦克风阵列的声源三维坐标估计问题,文中在TDOA(Time Difference of Arrival)声源定位算法中引入粒子群优化算法进行位置估计。利用PHAT(Phase Transform)加权函数的广义互相关法计算得到时延差的真实值,结合麦克风的坐标位置,通过几何关系计算出假设声源到达麦克风之间的时延差的估计值。设计时延真实值和估计值差值的平方和为粒子适应度函数,利用粒子群优化算法搜索空间中符合适应度函数的声源点,实现声源位置估计。仿真结果表明,在计算速度与球形插值法相近的情况下,文中所提算法比球形插值法具有更好的鲁棒性和抗噪性。
文摘The research on finding the arrival directions of speech signals by microphone arrny is proposed. We first analyze the uniform microphone array and give the design for microphone array applied in the hand-free speech recognition. Combining the traditional direction finding technique of MUltiple SIgnal Classification (MUSIC) with the focusing matrix method, we improve the resolving power of the microphone array for multiple speech sources.As one application of finding Direction of Arrival (DOA), a new microphone-array system for noise reduction is proposed. The new system is based on maximum likelihood estimate technique which reconstruct superimposed signals from different directions by using DOA information. The DOA information is got in terms of focusing MUSIC method which has been proven to have high performance than conventional MUSIC method on speaker localization[1].
