Blind estimation of reverberation time

The reverberation time (RT) is an important parameter for characterizing the quality of an auditory space. Sounds in reverberant environments are subject to coloration. This affects speech intelligibility and sound localization. Many state-of-the-art audio signal processing algorithms, for example in hearing-aids and telephony, are expected to have the ability to characterize the listening environment, and turn on an appropriate processing strategy accordingly. Thus, a method for characterization of room RT based on passively received microphone signals represents an important enabling technology. Current RT estimators, such as Schroeder's method, depend on a controlled sound source, and thus cannot produce an online, blind RT estimate. Here, a method for estimating RT without prior knowledge of sound sources or room geometry is presented. The diffusive tail of reverberation was modeled as an exponentially damped Gaussian white noise process. The time-constant of the decay, which provided a measure of the RT, was estimated using a maximum-likelihood procedure. The estimates were obtained continuously, and an order-statistics filter was used to extract the most likely RT from the accumulated estimates. The procedure was illustrated for connected speech. Results obtained for simulated and real room data are in good agreement with the real RT values.     

Effects of reverberation on perceptual segregation of competing voices

Two experiments investigated the effect of reverberation on listeners' ability to perceptually segregate two competing voices. Culling et al. [Speech Commun. 14, 71-96 (1994)] found that for competing synthetic vowels, masked identification thresholds were increased by reverberation only when combined with modulation of fundamental frequency (F0). The present investigation extended this finding to running speech. Speech reception thresholds (SRTs) were measured for a male voice against a single interfering female voice within a virtual room with controlled reverberation. The two voices were either (1) co-located in virtual space at 0 degrees azimuth or (2) separately located at +/-60 degrees azimuth. In experiment 1, target and interfering voices were either normally intonated or resynthesized with a fixed F0. In anechoic conditions, SRTs were lower for normally intonated and for spatially separated sources, while, in reverberant conditions, the SRTs were all the same. In experiment 2, additional conditions employed inverted F0 contours. Inverted F0 contours yielded higher SRTs in all conditions, regardless of reverberation. The results suggest that reverberation can seriously impair listeners' ability to exploit differences in F0 and spatial location between competing voices. The levels of reverberation employed had no effect on speech intelligibility in quiet.     

混响环境下汉语语音知觉特征的实验分析

根据混响环境下的汉语单音节清晰度实验,采用多维尺度和聚类分析的方法得到了混响作用下声母、韵母的知觉空间结构和层次逻辑关系。发现混响环境下声母的主要知觉特征是舌的发音部位(摩擦部位)和送气一不送气,其中舌的发音部位是声母最重要的知觉特征;韵母的主要知觉特征是起始部分元音的舌位。声母的清一浊特征和韵母的韵尾在混响环境下对语音知觉几乎不起作用。实验结果也揭示出语音的知觉特征与物理传递条件的相关性。     

Studies on techniques of non-Rayleigh oceanic reverberation suppression

The sonar systems which work in shallow water environment suffer greatly from influences of oceanic noises,acoustic propagation seesaw and multipath.With shallow water environment and higher range-bearing resolution of sonar systems,there are not enough independent scatterers within a resolution cell for the central limit theorem to hold.The reverberation envelope probability density function(pdf) diverges from Rayleigh pdf.The non-Rayleigh pdf with heavier tails is complicated,and it is difficult to estimate the function parameters accurately in real time.With CFAR(Constant False Alarm Rate) processing of the reverberation envelope data,which attenuates the heavier tails data values to the estimated background power values,the data reverberation is transformed from non-Rayleigh distribution to approximately Rayleigh distribution.Since it gets rid of the interferences which affect the estimation of background power,the detector can estimate the oceanic background power level more accurately.With the rational estimation of background power level,the CFAR detection capability is better and robust.With processing of high resolution sonar data,it is shown that the proposed algorithm is efficient.     

非瑞利海洋混响抑制技术研究

随着主动声呐距离及角度分辨率的提高,海洋混响包络概率密度函数不再是瑞利分布,而是函数分布后端较瑞利分布具有严重拖尾性的非瑞利分布。但非瑞利分布模型的概率密度函数复杂,参数估计困难。通过对非瑞利分布混响进行恒虚警率检测处理,将严重拖尾部分数据值衰减为背景均值,从而将非瑞利分布混响信号转化为近似瑞利分布。由于去掉了对背景功率估计影响较重的干扰,并基于瑞利分布模型进行目标检测,本文目标检测方法具有较好的鲁棒性和计算简单等优点。文中对一组高分辨率声呐数据进行了恒虚警率检测,结果验证了方法的有效性。     

Revisiting perceptual compensation for effects of reverberation in speech identification

Listeners were given the task to identify the stop-consonant [t] in the test-word "stir" when the word was embedded in a carrier sentence. Reverberation was added to the test-word, but not to the carrier, and the ability to identify the [t] decreased because the amplitude modulations associated with the [t] were smeared. When a similar amount of reverberation was also added to the carrier sentence, the listeners' ability to identify the stop-consonant was restored. This phenomenon has in previous research been considered as evidence for an extrinsic compensation mechanism for reverberation in the human auditory system [Watkins (2005). J. Acoust. Soc. Am. 118, 249-262]. In the present study, the reverberant test-word was embedded in additional non-reverberant carriers, such as white noise, speech-shaped noise and amplitude modulated noise. In addition, a reference condition was included where the test-word was presented in isolation, i.e., without any carrier stimulus. In all of these conditions, the ability to identify the stop-consonant [t] was enhanced relative to the condition using the non-reverberant speech carrier. The results suggest that the non-reverberant speech carrier produces an interference effect that impedes the identification of the stop-consonant. These findings raise doubts about the existence of the compensation mechanism.     

高分辨率有源声呐强混响抑制技术研究

有源声呐分辨率的提高可以抑制混响,但也使声呐包络数据的统计分布偏离瑞利分布,而更接近拖尾较重的K分布。强散射体所带来的强混响的幅值一般较大,它们使统计分布拖尾更严重,表征K分布的形状参数也越小。强混响作为目标干扰,严重影响了背景功率估计的准确性,从而降低了目标检测的性能。本文基于模糊统计理论,首先提出了用于抑制强混响的模糊统计归一化处理方法;然后对强混响和模糊统计归一化处理如何影响声呐数据分布和CFAR(Constant false-alarm rate)目标检测性能进行了仿真、研究和分析,最后对基于模糊统计归一化处理的CFAR检测性能和传统CFAR检测性能进行了仿真比较。仿真结果表明强混响目标干扰能使K分布数据的形状参数变小,而模糊统计归一化处理可抑制强混响目标干扰,增大包络数据分布的形状参数,提高形状参数估计性能和CFAR检测性能。     

Blind estimation of reverberation time in classrooms and hospital wards

This paper investigates blind Reverberation Time (RT) estimation in occupied classrooms and hospital wards. Measurements are usually made while these spaces are unoccupied for logistical reasons. However, occupancy can have a significant impact on the rate of reverberant decay. Recent work has developed a Maximum Likelihood Estimation (MLE) method which utilises only passively recorded speech and music signals, this enables measurements to be made while the room is in use. In this paper the MLE method is applied to recordings made in classrooms during lessons. Classroom occupancy levels differ for each lesson, therefore a model is developed using blind estimates to predict the RT for any occupancy level to within ±0.07 s for the mid-frequency octave bands. The model is also able to predict the effective room and per person absorption area.Ambient sound recordings were also carried out in a number of rooms in two hospitals for a week. Hospital measurements are more challenging as the occurrence of free reverberant decay is rarer than in schools and the acoustic conditions may be non-stationary. However, by gaining recordings over a period of a week, estimates can be gained within ±0.07 s. These estimates are representative of the times when the room contains the highest acoustic absorption. In other words when curtains are drawn, there are many visitors or perhaps a window may be open.     

三维空时多波束方法在抗混响中的应用

根据混响散射元空间分布的特点,分析了方位角给定后混响谱展宽程度随距离的变化规律,指出在近距离处混响谱展宽严重。针对混响信号的空时特性,对空时多波束(STMB)处理方法进行了改造和扩展,提出了三维STMB方法,用来进行运动声呐混响的抑制。采用仿真混响数据对提出的算法进行了检验,结果表明,在数倍于海深的检测距离内,三维STMB方法能够取得比STMB和常规方法更好的检测效果。     

相继脉冲混响中非相关成分的分析及其抑制

沉底目标探测实验时,相继脉冲混响之间存在非相关成分。结合混响时-频谱图分析,给出了引起相继脉冲混响之间非相关成分的影响因素。根据概率论中的大数定律,采用了一种相继脉冲混响积累抵消的方法以对非相关成分进行抑制。通过对实验数据的分析结果表明,所用方法可以抑制混响之间的非相关成分,使时-频谱图中混响背景变的更加均匀,有利于目标信号的检测。     

改进次最佳检测在侧扫声呐底混响抑制中的应用*

侧扫声呐进行沉底小目标探测时,底混响是主要背景干扰。底混响通常是一种非平稳、非高斯的带限噪声,它使得白噪声条件下的滤波器性能受到限制。在混响背景下常利用自回归模型对接收信号进预行白化处理,但对于实际侧扫声呐应用,白化后直接匹配滤波的处理效果不甚理想。针对此问题,在自回归模型预白化的基础上,提出采用一种次最佳检测与多分辨二分奇异值分解相结合的改进方法。该方法首先对接收信号进行分段处理,利用改进Burg算法估计每段数据自回归模型的系数及阶数;然后构造白化滤波器对分段数据预白化,并对白化后的数据进行多分辨二分奇异值分解;最后应用ostu方法对原始声图和处理后的声图进行目标检测。仿真与实验结果表明,该方法明显提高了信混比,改善了侧扫声呐沉底静态小目标的成图质量,有利于后期实现基于图像的目标自动检测。     

浅海混响建模的声束跟踪理论

研究建立了基于声束跟踪理论的浅海混响强度计算方法和混响时间序列仿真方法。给出了混响强度计算的简要理论推导,并进行了模型计算值与实验值的比较。建立了一种混响时间序列仿真模型,给出了其实现框架和方法。结合实验数据与文献研究结果,进行了混响序列相关特性的检验与分析。结果表明:建立的混响强度计算模型能很好地进行浅海混响强度的预报,混响序列仿真模型能仿真具有不同包络分布的混响序列,且其相关特性符合实验与文献研究结果。     

Modeling of reverberation in shallow-water based on the beam tracing theory

A reverberation intensity model and a reverberation series model in shallow-water based on the beam tracing theory were presented.The brief theoretical deduction to compute reverberation intensity was given,and the results were compatible with the measured data. The reverberation series simulation method was built and its characteristics were tested with the measured data and other results that had been verified.The studies show that the reverberation intensity model can be used to forecast shallow-water reverberation intensity,and the reverberation series simulation method can generate reverberation series which mostly properties, such as probability distribution,time-varying spectrum,and spatial correlation,agree well with the measure and the theory.     

早晚期混响划分对理想比值掩蔽在语音识别性能上的影响

真实环境中存在的噪声和混响会降低语音识别系统的性能。封闭空间中的混响包括直达声、早期反射和后期混响3部分,它们对语音识别系统具有不同的影响.我们研究了早期反射和后期混响的不同划分方法,以其中的早期反射为目标语音,计算出了不同的理想比值掩蔽并研究了它们对语音识别系统性能的影响;在此基础上,利用双向长短时记忆网络(BLSTM)估计理想比值掩蔽,测试它们对语音识别系统性能的影响.实验结果表明,基于Abel早期反射和后期混响的划分方法,理想比值掩蔽能够降低词错误率约2.8%;基于BLSTM的估计方法过低估计了理想比值掩蔽,未能有效提高语音识别系统的性能。     

基于感知对比度的图像清晰度客观评价模型

图像清晰度是评价图像质量时常用的指标之一。现有的清晰度评价模型未能充分考虑人眼视觉的亮度掩盖特性。为此,在均方根对比度基础上,考虑人眼亮度掩盖特性,通过计算图像中人眼感兴趣区域(包含细节、边缘和纹理)的感知对比度构造一种无参考的图像清晰度客观评价模型。并利用IVC数据库来验证模型,结果表明,与已有的4种清晰(模糊)度评价模型相比,该模型的评价结果更接近人眼主观感受,且计算量小,运算耗时短,是一种简单有效的图像清晰度评价模型。     

人耳听觉相关代价函数深度学习单通道语声增强算法

均方误差函数是深度学习单通道语声增强算法最常用的一种代价函数。然而,均方误差值的大小与语声质量好坏并非完全相关。为了提高算法性能,该文在深度神经网络训练中引入了两类与人耳听觉相关的代价函数。第一类是加权欧氏距离代价函数,考虑了人耳听觉掩蔽效应;第二类是Itakura-Satio代价函数、COSH代价函数和加权似然比代价函数,强调语声谱峰的重要性,侧重于恢复干净语声谱峰信息。基于长短期记忆网络结构分析比较了两类代价函数在深度学习单通道语声增强算法中的性能,并与均方误差代价函数进行对比。实验结果表明,基于加权欧式距离代价函数的深度神经网络单通道语声增强算法能够获得更好的语声质量和更低的噪声残留。     

基于人工神经网络的混响时间预测方法

在分析混响时间的各种影响因素的基础上,运用人工神经网络的BP算法,建立了厅堂混响时间的预测模型,该方法具有速度快、使用方便、精度高、可考虑的因素多等特点,具有一定的工程实用价值,有待实践的考验并逐步提高完善。     

混响背景下低秩矩阵恢复的目标亮点特征提取

有源声呐探测水下目标时,混响干扰增加了从目标回波信号中提取目标亮点特征的难度.依据目标回波与混响在时频域上能量分布的相关性不同,采用自适应核时频分析方法将目标回波信号变换到时频域上进行分析.通过低秩矩阵恢复方法将目标回波与混响分到稀疏矩阵和低秩矩阵中,从而分离目标回波与混响,降低混响对回波信号的干扰.针对稀疏矩阵采用Hough变换提取回波中的亮点峰,得到目标的亮点特征。通过仿真和实验数据证明在较低信混比情况下通过低秩矩阵恢复方法能够在时频域上进一步区分目标回波与混响,达到抑制混响的目的,便于获取目标亮点特征。     

可靠声路径传播特性及目标定位方法研究现状

提出了一种混响抑制方法以抑制深海环境中的混响干扰。基于时空谱矩阵中信号(混响和目标)旁瓣的低秩性与主瓣的稀疏性差异, 将混响抑制问题建模为矩阵的低秩、稀疏和扰动三项分解。采用格拉斯曼流型计算混响低秩空间, 并对稀疏矩阵稀疏性进行约束, 提出了一种混响快速抑制方法。基于随机正交模型与随机稀疏模型仿真分析了所提方法的有效性。结合南海实测深海混响数据和目标仿真信号对所提方法的有效性进行了实验验证。结果表明, 与已有的序列随机投影子空间追踪与稀疏滤波(SRPSS)方法相比, 所提方法的混响抑制性能相似, 但耗时减少可达55%。

     

基于柔性屏蔽材料混响室的设计与应用

利用柔性屏蔽材料不平整性使屏蔽腔内场环境易于满足各向同性、均匀分布、随机极化统计特征的特点,研究了三种不同柔性屏蔽材料搭建的模式搅拌混响室的可行性。在Z字形搅拌器的作用下通过测量得到低频场均匀性和高频归一化电场的概率密度函数,根据IEC 61000-4-21-2011标准和理想混响室模型验证了所搭建混响室的有效性。在此基础之上,通过实验测量分析了搅拌器转速、天线高度、天线位置对归一化电场概率密度函数(PDF)的影响,并利用所搭建混响室对加载开孔电大金属腔的电磁屏蔽效能进行了测试。研究结果表明利用柔性屏蔽材料搭建混响室具有较好的可行性。