Simulating the effect of acoustic treatment types for residential balconies with road traffic noise

Development of design guides to estimate the difference in speech interference level due to road traffic noise between a reference position and balcony position or façade position is explored. A previously established and validated theoretical model incorporating direct, specular and diffuse reflection paths is used to create a database of results across a large number of scenarios. Nine balcony types with variable acoustic treatments are assessed to provide acoustic design guidance on optimised selection of balcony acoustic treatments based on location and street type. In total, the results database contains 9720 scenarios on which multivariate linear regression is conducted in order to derive an appropriate design guide equation. The best fit regression derived is a multivariable linear equation including modified exponential equations on each of nine deciding variables, (1) diffraction path difference, (2) ratio of total specular energy to direct energy, (3) distance loss between reference position and receiver position, (4) distance from source to balcony façade, (5) height of balcony floor above street, (6) balcony depth, (7) height of opposite buildings, (8) diffusion coefficient of buildings and (9) balcony average absorption. Overall, the regression correlation coefficient, R², is 0.89 with 95% confidence standard error of ±3.4 dB.     

Accuracy of speech transmission index predictions based on the reverberation time and signal-to-noise ratio

This paper examines the accuracy of the speech transmission index (STI) calculated from the reverberation time (T) and signal-to-noise ratio (L_SN) of enclosed spaces. Differences between measured and predicted STIs have been analysed in two rooms (reverberant vs. absorbent), for a wide range of absorption conditions and signal-to-noise ratios (sixteen tests). The STI was measured using maximum length sequence analysis and predictions were calculated using either measured or predicted values of T and L_SN, the latter assuming diffuse sound field conditions. The results obtained for all the conditions tested showed that STI predictions based on T and L_SN tend to underestimate the STI, with differences between measured and predicted STIs always lower than 0.1 (on a 0.0–1.0 scale), and on average lower than 0.06. According to previous research, these differences are noticeable and therefore non-negligible, as 0.03 is the just noticeable difference in STI. The use of either measured or predicted values of T and L_SN provided similar STI predictions (i.e. non-noticeable changes), with differences between predictions that are on average lower than 0.03 for the absorbent room, and lower than 0.01 for the reverberant room.     

超大容量语音系统的存贮方法研究

提出了语音合成技术实现时的容量存贮问题,简要介绍了语音参数合成法中较优秀的线性预测编码方法,指出了它在实际应用中存在的困难,介绍了美国TI公司两种改进的预测编码算法MELP和CELP及相应硬件MSP50X3X系列语音合成器的原理,提出了一个应用系统实例,给出了详细的硬件和软件设计。     

基于任意麦克风阵列的近场声源三维定位算法研究

基于麦克风阵列的声源定位技术在通信、语音处理等领域得到广泛的应用。本文从声音传播的基本原理出发,推导出了精确的相对幅度衰减因子,获得了更加准确的信号传播模型。利用该模型并结合子空间算法的思想,提出了适用于任意拓扑结构的麦克风阵列的近场宽带三维声源定位算法。仿真结果表明,该算法在一维均匀直线阵、二维均匀圆阵和三维均匀球面阵中,均能够得到较好的定位效果。     

基于改进的蛙跳算法与支持向量机的实用语音情感识别

支持向量机是一种基于统计学习理论的新型机器学习算法,在高维特征空间中寻找最优分类超平面,具有很好的分类精度和泛化性能。支持向量机的训练需要求解一个带约束的二次规划问题,针对数据规模很大情况下经典训练方法变得很困难的缺点,提出一种基于改进混合蛙跳算法的支持向量机分类器参数优化方法,既提高了混合蛙跳算法的收敛速度和精度,又能借助混合蛙跳算法的全局随机搜索能力,为支持向量机参数的优化选择提供一条有效途径。本文提取情感语句的韵律特征、音质特征和混沌特征参数,提出一种基于改进蛙跳算法的数据融合方法,并利用基于改进蛙跳算法的支持向量机进行实用语音情感的识别研究。在实验中比较了PCA方法、BP神经网络和数据融合方法用于语音情感识别的识别率,研究结果表明本文所提的各项改进机制能有效提升情感识别率,为实用语音情感的识别提供一种新方法和新思路。      

基于自相关观测的语音信号压缩感知

本文基于压缩感知技术,根据语音信号的特点,提出了一种基于自相关特性的截断循环自相关矩阵作为观测矩阵,并在此基础上,从实用的角度出发,提出了基于模板匹配的近似截断循环自相关矩阵作为观测矩阵,并证明其满足RIP特性。由语音信号与截断循环自相关矩阵、近似截断循环自相关矩阵和高斯随机矩阵分别构造相应的观测,采用BP算法来重构原始语音信号。实验表明,由2个模板元素线性组合而成的近似截断循环自相关矩阵重构原始语音信号的性能与截断循环自相关矩阵的重构性能相当,且优于经典高斯随机矩阵,而且在相同的重构性能下,其压缩比远大于高斯随机观测矩阵,对语音信号的压缩性能有了明显地提高。      

基于MIM_LB算法的连续数字语音识别

互信息匹配模型依据互信息理论而提出，在语音识别中已经显示了良好的性能，文章在互信息匹配理论的现有成果的基础上，提出了基于互信息估计的连续语音识别算法MIM_LB算法，实验表明提出的算法简单有效．优于传统的LB算法。     

基于多流多状态动态贝叶斯网络的音视频连续语音识别

语音和唇部运动的异步性是多模态融合语音识别的关键问题,该文首先引入一个多流异步动态贝叶斯网络(MS-ADBN)模型,在词的级别上描述了音频流和视频流的异步性,音视频流都采用了词-音素的层次结构.而多流多状态异步DBN(MM-ADBN)模型是MS-ADBN模型的扩展,音视频流都采用了词-音素-状态的层次结构.本质上,MS-ADBN是一个整词模型,而MM-ADBN模型是一个音素模型,适用于大词汇量连续语音识别.实验结果表明：基于连续音视频数据库,在纯净语音环境下,MM-ADBN比MS-ADBN模型和多流HMM识别率分别提高35.91%和9.97%.     

A novel covert speech communication system and its implementation

In this paper, a Covert Speech Telephone （CST） is designed and implemented based on the information hiding technique, which works on the internet. To solve the large embedding capacity problem for real-time information hiding, a steganographic system combined with a watermarking scheme is proposed, which skillfully transfers the secret speech into watermarking information. The basic idea is to use the speech recognition to significantly reduce the size of information that has to be transmitted in a hidden way. Furthermore, an improved DFT watermarking scheme is proposed which adaptively chooses the embedding locations and applies the multi-ary modulation technique. Based on the GUI （Graphical User Interface） software, the CST operates on both ordinary and secure mode. It is a completely digital system with high speech quality. Objective and subjective tests show that the CST is robust against normal signal processing attacks and steganalysis. The proposed scheme can be used in terms of military applications.     

基于频域逐级回归的声学回声控制

传统声学回声控制算法一般采用基于随机梯度法更新的频域分块自适应滤波(PBFDAF)方法,但在以语音为主要回声信号的室内混响环境中,由于回声路径不稳定,往往收敛速度较慢,难以实现足够的回声抑制。该文提出一种基于频域逐级回归的声学回声控制算法。通过逐级回归分析远端信号和麦克风信号之间的线性关系,可以在保持较小的偏差的同时实现收敛较快的系统估计。同时,由于逐级分析了两通道间的短时相干性,因而该算法无需像常见方法一样,额外进行基于通道间相干函数的残余回声抑制或双讲检测,从而保持系统的紧凑性。若进一步假定近端背景噪声准平稳,则可利用基于近端信号非平稳程度的自适应平滑因子,在实现系统估计快速收敛的同时确保其稳定性。实验表明,该方法在常见的近端环境噪声水平下,在收敛速度和稳态误差上相对传统方法有显著优势,非常适合应用在室内远讲模式下的声学回声控制中。