基于统计的近场声源定位方法

基于麦克风阵列的声源定位技术可以广泛应用于音视频会议、说话人跟踪与识别以及助听器等众多场合中。根据语音信号的短时平稳特性,文中提出了一种改进的基于MUSIC算法进行声源二维定位的方法。该方法按帧交叉进行声源数估计和声源方位估计,最后对多帧信号的估计值进行统计、平均得到最终的方位估计和较准确的声源数估计。仿真结果表明,这种方法能有效解决由于声源数估计不准确导致的峰值搜索时偏差较大的问题,并且具有良好的抗噪性能。     

一种适用于助听器的低失调自适应指向性算法

在噪声环境中助听器的性能会受到严重影响.但当噪声与期望信号处在不同方向时,在助听器中使用指向性传声器系统能够有效地抑制噪声,使助听器的使用者受益.本文基于自适应LMS(最小均方)算法提出了一种适用于助听器的低失调自适应指向性算法,用以动态调整传声器系统中滤波器的系数,使指向性模式的灵敏度最低点朝向噪声源方向,达到降噪的目的.相比于现有的LMS算法,本文引入了一种后验信噪比并将与其相关的信噪比补偿因子引入自适应步长的更新过程,有效改善了语音信号存在时的失调情况.最后,本文通过仿真验证了本文算法对失调的改善作用.     

A fast search method of steered response power with small-aperture microphone array for sound source localization

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. Ex- periments 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 conven- tional 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.     

数字助听器中单通道语音增强算法的研究

传统多通道补偿算法忽略保护语音特征,容易造成语音结构变形和识别率低等问题。为了解决上述问题,本文提出了一种基于多分辨率小波的单通道语音增强算法。利用多分辨率小波对信号进行分解与重构,提取出语音信号的频谱包络,得到特征点出其信息并依此计算补偿增益,再利用插值算法计算出整个频谱的增益并对其进行响度补偿。仿真实验以及主观性能测试的各项结果均表明该算法能够在对语音进行补偿的同时有效地保护语音特征,提高言语识别率,达到比较理想的效果。      

基于最小方差无偏估计的目标定位算法研究

广义互相关时延估计方法（GCC）由于具有计算简单和易于实现的特点,因此在实际的被动声源定位系统中得到了广泛应用。随后出现了不同加权函数的GCC定位算法,但是在不同环境中各个加权函数的选择不同,时延估计误差不同。提出了基于最小方差无偏估计（MVU）的时延估计算法,对多种加权函数下的时延估计建立数学模型,然后用最小方差估计出最优的时延估计值。仿真实验表明,这种方法使估计精度明显提高。     

用于视频监控的特定声实时定位系统

设计了一种用于视频监控的具有较强抗干扰能力的特定声定位实时系统。本系统利用广义互相关算法(GCC)估计声音到达2个传声器的时间差(TDoA),以此计算声源的方向角。本系统具有特定声检测功能,只有特定声出现时才输出定位结果,提高了系统的抗干扰能力。实验证明,该系统能够实时地对枪声进行定位,当枪声在±30°范围的时候,室内测试的定位误差在±3°以内;室外测试定位误差在±5°以内。     

基于小波变换模极大值重构原理的HRTFs平滑逼近预处理

空间听觉的研究以及虚拟听觉空间的实现中,与头相关传递函数(Head-Related Transfer Functions, HRTFs)或与头相关冲激响应(Head-Related Impulse Responses, HRIRs)的高效建模对于隐含在HRTFs中的特征模式的识别有着极其重要的作用。作为建模前的一个重要环节,该文通过对HRTFs的时域奇异性特征分析和全部测量空间方位上HRIRs分布特点的统计判断,采用具有平移不变特性的多孔小波变换和相应的模极大值重构原理提出了一种HRTFs非线性平滑逼近预处理的方法。仿真实验结果表明,在设置的阈值门限一致的情况下,该文方法较PCA(Principal Component Analysis)和基于小波变换Mallat算法的逼近处理的性能分别提高了8.3dB和2.4dB。     

闪电声源定位系统研究

所研制的闪电声源定位系统由四元正方形麦克风声阵列、雷声信号传输系统和信号采集、记录与显示设备等部分组成.结合一次地闪雷声实测数据,采用广义互相关时延估计法计算了雷声信号到达不同麦克风的时间差,依据声光差定距法获得了声源点与麦克风阵列的距离,实现了雷电声源点的三维定位和闪电放电通道的三维重构.通过与同步观测到的雷电电磁脉冲场及大气电场进行对比,表明系统的定位效果较好.     

Reverberation multi-source localization algorithm based on compressed sensing with dual microphones

In traditional multi-source localization field,it is necessary to guarantee that the number of microphone is more than the number of source.To overcome this constraint,a dual-microphone multi-source localization algorithm based on CS was proposed,where the number of sound source localized successfully was more than 3.The multi-source localization was regarded as the block sparse signal reconstruction in this algorithm,and the full room impulse responses normalized were exploited to construct the compressed observation matrix in frequency domain.In reconstructed block sparse signal,the positions of non-zero blocks were corresponded to the positions of sound sources in space.The simulation shows that compared with the SRP-sub algorithm,in reverberation time 0.6s with dual-microphone,the proposed multi-source localization algorithm based on compressed sensing has higher capability which can reach 80% success rate by using 40 frequency points to localize 3 sound sources.     

基于遗传算法的声源三维定位方法

相位变换加权的可控响应功率（SRP-PHAT）算法是一种基于麦克风阵列的鲁棒声源定位方法,该算法在有混响和噪声的环境下仍有较高的定位精度.但该算法用网格法对整个声源空间进行搜索,逐点计算其目标函数,因而总的计算量非常大,不适用于实时定位系统.针对SRP-PHAT的特点,采用遗传算法进行搜索,使总的计算量大幅度降低.仿真结果表明在混响时间为300ms,信噪比为5dB的条件下,该算法仍可达到较高的定位精度.     

Efficient video coding based on audio-visual focus of attention

This paper proposes an efficient video coding method using audio-visual focus of attention, which is based on the observation that sound-emitting regions in an audio-visual sequence draw viewers’ attention. First, an audio-visual source localization algorithm is presented, where the sound source is identified by using the correlation between the sound signal and the visual motion information. The localization result is then used to encode different regions in the scene with different quality in such a way that regions close to the source are encoded with higher quality than those far from the source. This is implemented in the framework of H.264/AVC by assigning different quantization parameters for different regions. Through experiments with both standard and high definition sequences, it is demonstrated that the proposed method can yield considerable coding gains over the constant quantization mode of H.264/AVC without noticeable degradation of perceived quality.     

基于人耳听觉特性的助听器响度补偿策略

设计面向老年性听力损伤患者的数字式助听器,对语音信号进行响度补偿时需要同时兼顾频率与声强级。针对人耳听觉的这一特性,归纳提出了动态压缩响度补偿策略。同时分别从对患耳敏感的低频域和高频域语音两个层面深入进行Matlab仿真验证。结果表明,此研究对于保证数字式助听器中响度补偿效果的合理性以及完整性具有重要意义。     

基于视觉、听觉系统的声源水平方位定位

针对空间声源水平方位定位的精度问题,提出了利用基于软域值的小波分析方法对声源信号进行去噪处理.在此基础上,利用机器人的听觉系统对目标声源的水平方位进行粗定位;通过双目立体视觉系统对粗方位进行一定的矫正、补偿,实现方位的精定位.实验证明,提出的由粗到精的定位策略和方法具有较高的定位精度.     

基于频率信噪比加权的麦克风阵列声源定位算法

为了提高噪声和混响环境下麦克风阵列的声源定位算法性能,提出了一种基于频率信噪比加权的可控响应功率定位算法。该算法首先根据每帧阵列信号的频域协方差矩阵估计每个频率的信噪比;然后通过激活函数将频率信噪比映射为加权值,并修正传统的相位变换可控响应功率计算公式;最后利用修正公式计算每个候选位置的可控响应功率值,通过搜索可控响应功率的最大值实现声源定位。该算法根据实时估计的频率信噪比自适应地调整各频率分量对可控响应功率的贡献。仿真结果表明,与传统的相位变换可控响应功率算法、维纳预滤波波束形成算法相比,在噪声和混响的复杂声学环境下,本文算法的定位正确率更高,均方根误差更小,对噪声的鲁棒性更强。      

一种基于小波多尺度边缘检测的图像融合算法

该文提出了一种新的基于多尺度边缘检测的小波图像融合方法,是一种利用图像边缘特征的小波图像融合方法,融合过程利用了图像的多尺度边缘信息。为了更好地保持图像的边缘,该文在图像融合过程中将图像去噪与边缘检测相结合。提出了一种物理意义明确的小波最佳分解层数的确定方法。利用统计分析的评判准则,如熵、标准偏差等,评价二维多聚焦图像不同小波分解层的融合效果,表明该方法提高了图像的熵和标准偏差的值,算法效果良好。     

On wavelet denoising and its applications to time delay estimation

The application of dyadic wavelet decomposition in the context of time delay estimation is investigated. We consider a model in which the source signal is deterministic and the received sensor outputs are corrupted by additive noises. Wavelet denoising is exploited to provide an effective solution for the problem. Denoising is first applied to preprocess the received signals from two spatially separated sensors with an attempt to remove the contamination, and the peak of their cross correlation function is then located from which the time delay between the two signals can be derived. A novel wavelet shrinkage/thresholding technique for denoising is introduced, and the performance of the algorithm is analyzed rigorously. It is proved that the proposed method achieves global convergence with a high probability. Simulation results also corroborate that the technique is efficient and performs significantly better than both the generalized cross correlator (GCC) and the direct cross correlator (CC)     

声场空频特征非参数融合无人机声学探测

针对复杂多源混叠的目标声源辨识问题,传统定位算法因为目标信号中混有较多干扰噪声,定位结果会出现很多野点,无法准确地对目标进行估计。本文提出利用高分辨率声成像处理算法获得目标区域声场空频信息矩阵,依据先验的目标噪声源频率统计特性,通过非参数估计的Parzen窗函数法计算空间分布概率密度函数,基于目标在特征频段和空间区域的分布特性,建立空频特征联合优化的检测定位模型。无人机声学检测仿真与实际定位结果表明该方法具有良好的空间抗干扰能力,可实现复杂环境下声源目标的检测定位。      

一种修正的近场声源定位时延估计方法

时延估计是近场声源定位领域中的一项关键技术。相位转换广义互相关时延估计方法（PHAT-GCC）由于其低的计算复杂度和易于实现的特点使得此方法在实际的被动声定位系统中得到了广泛应用。但是此方法只能在高信噪比和适度混响条件下有较好的性能。针对此问题,给出了一种修正的PHAT—GCC方法。并在不同信噪比和混响环境下与PHAT—GCC方法进行比较,仿真实验表明,修正的方法在较低信噪比下的抗混响性能有所提高。     

Near-field localization algorithm of multiple sound sources based on approximated kernel density estimator

For near-field localization of multiple sound sources in reverberant environments,a algorithm model based on approximated kernel density estimator (KDE) was proposed.Multi-stage (MS) of sub-band processing was introduced to effectively solve the spatial aliasing by wide spacing.Spatial likelihood function (SLF) was built for multi-dimensional fusion by using two operators,sum (S) and prod (P).Then four algorithms,S-KDE,P-KDE,S-KDEMS,P-KDEMS,were derived.By the comprehensive comparison of the two statistical indicators root mean square error (RMSE) and percentage of SLF (PSLF) which denoted the recognition,P-KDEMS is confirmed as a near-field localization algorithm of multiple sound sources with high robustness and recognition.     

Acoustic feedback cancellation based on weighted adaptive projection subgradient method in hearing aids

Acoustic feedback is an important factor that degrades the overall performance of hearing aids, and acoustic feedback cancellation has always been the research focus in the field of signal processing in hearing aids. The newly suggested adaptive projection subgradient method (APSM) for adaptive signal processing solves the problem of difficulty in finding the exact projection operator in the realization of affine projection by taking the subgradient projection hyperplane as the searching region for relaxed projection. This work applies APSM in the acoustic feedback cancellation system of hearing aids for the first time, and proposes a weighted adaptive projection subgradient method (WAPSM), which takes into consideration the exponential decay weight factor to incorporate the prior information of estimation system. The new method is compared with the traditional NLMS algorithm and APSM algorithm in simulation experiments. Incorporating the prior information of estimation system by setting the proper weighting matrix, WAPSM achieved notable improvements on the speed, stability and accuracy of the misalignment convergence. Numerical experiments demonstrate that the proposed algorithm is more robust for low SNR and real speech segment input than the traditional algorithms.