A nonlinear operator-based speech feature analysis method withapplication to vocal fold pathology assessment

Traditional speech processing methods for laryngeal pathology assessment assume linear speech production with measures derived from an estimated glottal flow waveform. They normally require the speaker to achieve complete glottal closure, which for many vocal fold pathologies cannot be accomplished. To address this issue, a nonlinear signal processing approach is proposed which does not require direct glottal flow waveform estimation. This technique is motivated by earlier studies of airflow characterization for human speech production. The proposed nonlinear approach employs a differential Teager energy operator and the energy separation algorithm to obtain formant AM and FM modulations from filtered speech recordings. A new speech measure is proposed based on parameterization of the autocorrelation envelope of the AM response. This approach is shown to achieve impressive detection performance for a set of muscular tension dysphonias. Unlike flow characterization using numerical solutions of Navier-Stokes equations, this method is extremely computationally attractive, requiring only a small time window of speech samples. The new noninvasive method shows that a fast, effective digital speech processing technique can be developed for vocal fold pathology assessment without the need for direct glottal flow estimation or complete glottal closure by the speaker. The proposed method also confirms that alternative nonlinear methods can begin to address the limitations of previous linear approaches for speech pathology assessment     

An automated carotid pulse assessment approach using Doppler ultrasound

During cardiac arrest emergencies, lay rescuers are required to manually check the patient's carotid pulse after the delivery of defibrillation shocks to assess the cardiac resuscitation progress of the patient. As a more automated way of monitoring the resuscitation progress, a new Doppler-ultrasound-based carotid pulse assessment approach is presented in this paper. The method works by analyzing the temporal aperiodicity of Doppler shifts seen in the ultrasound echoes returned from the patient's carotid arteries. As a quantitative investigation with this method, we derived a new measure called the pulselessness indicator to assess whether a carotid pulse is absent based on the given Doppler information. To study the performance of the new carotid pulse checking method, we built a multi-channel CW Doppler prototype device to acquire Doppler data in vivo during cardiac arrest experiments conducted on five different swines and computed pulselessness indicator estimates with these data. Our results indicated that the Doppler-based pulse checking approach has good sensitivity and specificity: it had a pulselessness detection rate greater than 0.9 for a given false alarm rate of 0.05. As a further analysis, the prototype device was applied to other experiments where the swine had suffered cardiac arrest for over five minutes. It showed a consistent assessment performance on the monitoring of the swine's resuscitation progress after defibrillation and chest compressions.     

语音端点检测在实时语音截取中的应用

语音端点检测在语音识别系统中占有重要地位。针对在噪声多变的环境中实时截取完整语音信号存在困难,文章提出一种实时语音端点检测方法。该方法首先提取每帧信号的短时平均过零率与Mel频率倒谱系数;然后利用前N帧背景噪声的Mel频率倒谱系数对当前帧进行归一化,并以该特征矢量的L2范数作为另一特征;最后根据多特征分析对有效语音信号进行截取。实验结果表明,该方法在多变的噪声环境中,截取完整语音信号具有较高准确率。     

Adaptive estimation of residue signal for voice pathology diagnosis

The use of noninvasive techniques to evaluate the larynx and vocal tract helps the speech specialists to perform accurate diagnose of diseases. In this study, a method to distinguish among 21 different pathologies using speech signals was developed. Through inverse filtering (Kalman and Wiener filters) of the voice signal, the residue was estimated and seven acoustic features were extracted from it to evaluate the laryngeal diseases. As time-invariant inverse filtering was used, the nonstationary nature of dysphonic voices was also considered. Together with the estimation of the acoustic features using a robust statistical method, this technique also allowed us to discriminate among pathologies with very close perceptual characteristics. The results from a Mann-Whitney test indicated that the best measurement for pathological discrimination was JITTER with 54.79% ability to cluster the voice types and the worst one was spectral flatness of residue (SFR) with 36.41%     

Quality assessment of speech coding and speech synthesis systems

The concept of speech quality assessment is examined. Quality assessment methodologies for speech waveform coding, source coding, and speech synthesis by rule from the viewpoints of naturalness and intelligibility are reviewed. Both subjective and objective measures are considered     

飞机语音告警系统语音库的建立

飞机语音告警系统语音信息的录制工作存在受人员、环境限制及操作繁琐等问题,本文提出了解决方案：建立了一种通用的语音报警系统语音库,阐明了该系统的基本原理、建立过程和人机交互的实现。     

Pipe inspection using a laser-based transducer and automated analysis techniques

This paper presents a new sensing methodology for the automated inspection of pipes. Standard inspection systems, as they are for example used in waste pipes and drains, are based on closed-circuit television cameras which are mounted on remotely controlled platforms and connected to remote video recording facilities. Two of the main disadvantages of such camera-based inspection systems are: 1) the poor quality of the acquired images due to difficult lighting conditions and 2) the susceptibility to error during the offline video assessment conducted by human operators. The objective of this research is to overcome these disadvantages and to create an intelligent sensing approach for improved and automated pipe-condition assessment. This approach makes use of a low-cost lighting profiler and a camera which acquires images of the light projections on the pipe wall. A novel method for extracting and analyzing intensity variations in the acquired images is introduced. The image data analysis is based on differential processing leading to highly-noise tolerant algorithms, particularly well suited for the detection of small faults in harsh environments. With the subsequent application of artificial neural networks, the system is capable of recognizing defective areas with a high success rate. Experiments in a range of waste pipes with different diameters and material properties have been conducted and test results are presented.     

基于语言表达障碍者的藏文语音辅助系统的设计

基于西藏地区语言表达障碍者迫切的实际需要和嵌入式语音播放系统的应用日益成熟和广泛,采用SPCE3200作为本系统的主控芯片,通过TFT LCD模组完成了藏文文本的输入和显示,根据一定算法直接调用存储在外扩Flash(SD卡)上的语音资源,利用SPCE3200自带的解码器,通过软件设计实现了藏文语音播报,旨在帮助广大藏族同胞中语言表达障碍者实现快捷方便有效的与外界的交流。实际使用结果表明,该系统反应速度快,运行稳定,可以直接通过触屏实现藏文的输入和语音播放,简单、快捷、方便。该系统作为藏族同胞语言表达障碍人群的语音辅助工具,极大的方便和改善了他们的生活质量,具有一定的实用推广价值。     

Autocorrelation analysis of speech signals using Fermat numbertransform (FNT)

A method for speedy computation of the autocorrelation coefficients used by linear predictive coding (LPC) that uses Fermat number transform (FNT) is described. It is found that there exists a fast computational algorithm for FNT which has a computational structure similar to the fast Fourier transform (FFT). Since the fast Fermat number transform (FFNT) and FFT have similar computational structures, readily available FFT VLSI hardware structures may be adopted for real-time implementation of the FFNT. A verification of the FFNT on an MC 68000 single-board computer has been performed with quite satisfactory results     

Observation of sea-ice dynamics using synthetic aperture radarimages: automated analysis

Two techniques for automated sea-ice tracking, image pyramid area correlation (hierarchical correlation) and feature tracking, are described. Each technique is applied to a pair of Seasat SAR sea-ice images. The results compare well with each other and with manually tracked estimates of the ice velocity. The advantages and disadvantages of these automated methods are pointed out. Using these ice velocity field estimates it is possible to construct one sea-ice image from the other member of the pair. Comparing the reconstructed image with the observed image, errors in the estimated velocity field can be recognized and a useful probable error display created automatically to accompany ice velocity estimates. It is suggested that this error display may be useful in segmenting the sea ice observed into regions that move as rigid plates of significant ice velocity shear and distortion     

话音波形异常指数在话音质量客观评价中的应用

给出了一个话音串音的检测方案，提出了话音波形异常指数(Speech Wave Abnormal Index，SWAI)的概念和算法。SWAI描述了受到损害的话音浊音部分的准周期性被破坏的程度。它的提出有效地解决了串音检测问题，同时将其应用于话音质量客观实时评价，取得了理想的效果。     

基于粒子滤波的静音检测与声源跟踪算法

基于粒子滤波的跟踪算法是解决说话人跟踪问题的一种常用方法.结合了静音检测技术的声源跟踪算法,在静音期间,主要靠声源动态方程来估计目标的位置,可有效地减小误差.传统的噪声环境中的静音检测算法计算量较大,不利于实时跟踪.该文利用声源跟踪中的粒子滤波算法实现静音检测,算法用每帧信号的粒子状态观测值方差来检测静音,简便而可靠.仿真结果表明,该算法能有效地减小静音期间的跟踪误差,且计算量不增加.     

A noise reduction technique of speech signal using ICA and spectral analysis

This paper discusses the new method on noise reduction exploiting the combined effects of wavelet decomposition, ICA and spectral analysis on noisy speech. The input noisy speech is wavelet decomposed into two signals. Wavelet entropy is computed based on the modified probability density function for the signal derived from the approximation coefficients during wavelet decomposition. By proper entropy comparison, the starting frame is detected. Between the two signals obtained from the wavelet decomposition, one is speech combined with noise and another one is noise alone. These two signals are analysed in independent component analysis (ICA) domain, in order to generate an enhanced speech. Zero-crossing rate is computed and used to discriminate between speech and noise. Then, spectral analysis is performed on the noise prior to starting frame and noisy speech. Elimination of noise frequencies in the noisy speech leads to noise reduced speech. Subjective analysis and experimental results show the considerable noise reduction capability of the proposed algorithm.     

On using non-linear canonical correlation analysis for voice conversion based on Gaussian mixture model

Voice conversion algorithm aims to provide high level of similarity to the target voice with an acceptable level of quality.The main object of this paper was to build a nonlinear relationship between the parameters for the acoustical features of source and target speaker using Non-Linear Canonical Correlation Analysis(NLCCA) based on jointed Gaussian mixture model.Speaker indi-viduality transformation was achieved mainly by altering vocal tract characteristics represented by Line Spectral Frequencies(LSF).T...     

基于Android语音识别的音响声控系统的研究与实现

基于Android平台的语音识别技术,结合WiFi语音指令进行识别,通过WiFi网络和嵌入式控制模块控制音响设备工作的音响声控系统。语音识别采用科大讯飞开放平台提供的语音识别SDK,WiFi网络由WiFi路由器提供,嵌入式控制模块采用STC15F204EA控制器,配合NL6621-M3 WiFi模块,接收处理指令。经过实验测试,音响系统能有效地通过语音进行控制,满足现代音响设备智能化的要求。     

Real-time automated risk assessment in protected core networking

Protected Core Networking (PCN) is an approach to creating a secure and flexible network and communications infrastructure that supports network enabled capability (NEC) operations. The real-time automated risk assessment (R-TARA) provides a theoretically and practically sound method for risk assessment in the Protected Core. The purpose of the R-TARA is multifold. On the one hand it provides a global metric, which could be used by the network operator to assess the overall security level of the network and its evolution over time. On the other hand, the results of R-TARA can be used in order to achieve dynamic accreditation. Finally, R-TARA local risk metrics, e.g. susceptibility to DoS attacks, can be used for dynamic routing decisions. We propose use of Bayesian networks, known from operational risk assessment, for PCN risk assessment and we provide analytical and simulative evaluation of R-TARA mechanisms.     

Real-time areagraph of continuous speech for analysis and speech training

As an alternative to the spectrograph technique for speech analysis, an areagraph technique is presented in which the instantaneous vocal-tract area function (derived from linear prediction analysis) is plotted against time with distance along the tract as the y-ordinate and area denoted by intensity modulation. Since the display is related to a physical quantity, it has a number of advantages over the spectrograph. An application to speech training is described.     

语音信号的加权mel倒谱分析

本文利用人耳的感知特性,提出了加权mel倒谱系数,并建立了相应的分析算法。实验结果表明,该系数不仅能够准确地刻画说话人声道的短时特征,还能用来重建出高质量的语音。因此加权mel倒谱分析不仅能够应用于语音识别和说话人识别,还能应用于语音编码和参数合成。