语音端点检测中能零比方法的改进

传统的基于语音信号短时能量与短时过零率之比的单参数双门限端点检测方法对高信噪比的语音信号能实现较好的检测,而在低信噪比的情况下检测正确率却很低。本文在研究了语音信号的非线性分析方法后,提出了一种改进的端点检测方法。首先,对分帧加窗后的每一帧带噪语音信号进行经验模态分解求其短时Teager能量;然后,求每一帧的短时过零率,平滑处理之后进行归一化;最后,求出短时Teager能量与归一化短时过零率之比用于端点检测。经过仿真实验证明,本文提出的改进方法能够在低信噪比的带噪环境下实现比传统能零比方法更好的端点检测效果。     

一种基于短时平均幅度差的语音检测算法

提出了一种利用语音信号的短时平均幅度差特征并结合短时平均幅度的语音检测算法。该算法在专用通信系统中,用以对接收到的电台信号进行分析,判断其中是否有语音信号,从而控制半双工电台的发射开关,使其处于接收或发射状态。实验表明,该算法能在较低的信噪比情况下准确地检测出语音信号,而且计算方法简单,硬件处理容易,可靠性高,能够满足实时系统的需要。     

低端DSP芯片的语音处理算法研究

介绍了一种利用TI公司的TMS320VC5402定点DSP芯片实现的基于语音能量、短时平均幅度差和过零率的语音检测器,给出了算法的详细设计过程和DSP硬件实现方案,该方案在专用通信系统中,用以对接收到的电台信号进行分析,判断其中是否有语音信号,从而控制半双工电台的发射开关,使其处于接收或发射状态。实验表明,该算法能在较低的信噪比情况下准确地检测出语音信号,而且计算方法简单,硬件处理容易,可靠性高,能够满足实时系统的需要,在对DSP在其他方面的应用也有一定的参考价值。     

基于自相关最大值和过门限率的语音端点检测

语音处理中,在噪声环境尤其是在非平稳噪音环境下进行端点检测是很困难的。在低信噪比的情况下,传统用于端点检测的特征参数不能充分描述语音信号的特征,导致端点检测的效果严重退化。为此,笔者从语音信号的时域或频域出发,提出了一种把短时自相关函数最大值和短时过门限率相结合的方法。实验表明,该方法弥补了自相关函数最大值方法和过零率的不足,提高了语音端点检测的性能。     

高脉冲噪声坏境中双门限法语音端点检测研究

语音端点检测是对有效语音段的识别关键技术,准确的端点检测使语音信号的后续处理计算量减少,有效地节约资源。现在多数语音端点检测技术例如能频值、谱熵、小波能量熵变换等都能准确检测出有效的语音段。文中介绍了一种双门限端点检测法,即利用短时平均过零率和短时平均能量法进行双门限检测,再设置一个最短时间门限,有效地在高脉冲噪声环境中准确识别汉语发音。通过与其他方法对比实验,文中双门限技术在短时高脉冲噪声环境下能有效提高语音识别率。仿真结果表明,端点检测正确率达93%。     

基于谱减法和均匀子带频带方差法的端点检测研究

传统的端点检测算法是基于短时能量和短时过零率的双门限检测法,该算法对于含噪语音信号检测效果不佳.因此,将谱减法与均匀子带频带方差算法相结合,结合算法分两个过程,首先用谱减法对带噪语音信号进行降噪,然后用均匀子带频带方差法进行端点检测.实验结果表明,结合算法对于含噪较多的语音信号检测效果良好.     

计算机语音信号处理与语音识别系统

对计算机语音处理和对单个数码字识别的实现进行了探讨。根据汉语语音的特点，以汉语单音字作为识别对象，对１０个数码字识别进行了研究和实验。通过观察和分析语音信号的时域特性（主要是短时帧能量、短时过零率和帧能量差），并把它们应用于语音端点检测，为系统的建立做了基础准备。选用了语音信号的功率谱差的特征，进行了模板的建立与识别实验。测试结果表明，该系统性能较稳定，单个数码字识别率可达９８．６％，说话人识别率     

一种改进的多特征值语音端点检测方法研究

为了提高语音识别系统中语音端点检测的准确性,提出一种改进的多特征值语音端点检测方法.新方法首先对信号进行小波分解及小波去噪处理,对去噪后小波子带系数进行短时能量与基音周期两特征值的提取,综合考虑两特征值的大小来进行语音端点检测.实验证明,改进的检测方法提高了端点检测的抗噪性及准确度.     

基于短时自相关及过零率的语音端点检测算法

传统的基于短时能量端点检测算法,在高信噪比环境下可以比较准确地检测出语音端点,但在低信噪比环境下检测效果不理想。文中提出了基于短时自相关最大值与短时过零率之积的改进算法。利用短时自相关最大值可以有效地区分出语音段和噪音段,利用短时过零率可有效地检测出清音信号,将两参数相结合可有效地检测出低信噪比语音信号的端点。实验证明,在低信噪比环境下该改进算法相比短时能量算法减小了检测误差,可以有效地检测出语音端点。     

基于TMS320F2812的短波电台语音处理系统设计

话音的降噪与静噪是短波无线电台的需要实现的重要功能之一.文章以TMS320F2812 DSP芯片为核心设计实现一种能在短波转接电台中使用的语音降噪、静噪处理系统.首先,利用最小均方(LMS)误差自适应滤波算法对短波电台接收到的可能含有语音和噪声的信号进行消噪处理,得到较高信噪比的接收信号.然后,在噪声信号背景下应用短时自相关算法检测接收信号中是否含有语音,从而实现短波电台的数字静噪功能.通过对系统硬件电路和信号处理算法的测试,该系统能较好地完成短波电台接收信号的语音检测与处理功能.     

Design and implementation of a robust pitch detector based on aparallel processing technique

The design and implementation of a parallel-processing-based pitch detector is presented. Pitch information is extracted by performing pitch detection on four different waveforms derived from the speech signal. Pitch information from the four pitch-detection processes is then combined to determine a final pitch estimate. The performance of this pitch detector is evaluated on a large database and compared to other well-known pitch detection algorithms. It has been implemented in real time on a TMS32020 fixed-point digital signal processor as part of a 2.4 kb/s vocoder. A performance comparison of the real-time fixed-point implementation and a computer simulation are also given. The results show that the pitch detector performance is maintained in the real-time implementation mainly because the majority of the algorithm computations are integer arithmetic and logic-type operations     

A single-chip NMOS analog front-end LSI for modems

Presents a fully integrated analog front-end LSI chip which is an interface system between digital signal processors and existing analog telecommunication networks. The developed analog LSI chip includes many high level function blocks such as A/D and D/A converters with 11 bit resolution, various kinds of SCFs, an AGC circuit, an external control level adjuster, a carrier detector, and a zero crossing detector. Design techniques employed are mainly directed toward circuit size reductions. The LSI chip is fabricated in a 5 /spl mu/m line double polysilicon gate NMOS process. Chip size is 7.14/spl times/6.51 mm. The circuit operates on /spl plusmn/5 V power supplies. Typical power consumption is 270 mW. By using this analog front-end LSI chip and a digital signal processor, modern systems can be successfully constructed in a compact size.     

基于FPGA的实时基音周期估计系统

提出一种基于现场可编程门阵列FPGA的实时基音周期估计系统。语音信号先通过模数转换器转换成无符号位的8-bit的语音数字信号,然后,对每一帧语音信号进行电平削波,并将削波后的语音信号转换为带符号位的2-bit的数字信号,再采用自相关函数方法估计语音信号的基音周期,对一帧带符号位的2-bit的数字信号做自相关运算能够转换为简单的加法运算,只要用简单的组合逻辑电路和计数器就能够实现。使用SpartanIIXC2S30芯片将实时的基音周期估计算法用芯片内的存储器、门电路和时序电路实现,达到实时基音周期估计的目的。     

Real-Time Implementation of Time Domain Harmonic Scaling of Speech for Rate Modification and Coding

Time domain harmonic scaling (TDHS) has been realized in real time on the Bell Laboratories digital signal processing (DSP) integrated circuit. It is an algorithm that can expand or compress the bandwidth and sampling rate of speech by taking advantage of the pitch structure in the speech signal. As such it is useful in a variety of speech applications including speech coding, speech enhancement, and rate modification. A single DSP can perform compression and a second DSP can perform expansion. Both operations require pitch information to be supplied with the input speech. Included in the system is a real-time pitch/periodicity detector which has also been implemented on a single DSP. Its design is based on a novel modification of the autocorrelation function type pitch detector. This paper presents details of both the TDHS and pitch detector implementation and discusses their performances. In particular in this paper we discuss a 2:1 compression and expansion system that has been used as part of a 9.6 kbit/s speech coder. TDHS was previously thought to require a much larger buffer than the RAM memory available in the DSP. We show that for all the compression/expansion ratios of interest the buffer size needed is twice the maximum pitch period.     

ML7204和PicoBlaze软核处理器实现低速话音编解码系统

语音信号压缩编码是数字语音信号处理的主要方面．在现有的语音编码中,G．729A算法在8kb／s的码率下取得了较好的语音质量,具有广阔应用前景,因此提出采用PicoBlaze和ML7204实现G．729A语音压缩／解压详细的软硬件实现方案,并描述了G．729A语音编解码器ML7204的工作原理、性能、接口,以及FPGA内嵌IP核微处理器PicoBlaze的特点和使用方法。给出硬件电路设计原理,以及各部分的具体实现方法和原理图。并给出软件流程和主要代码。实验结果表明,系统提供话音点到点的时延仅为25mS,而语音质量平均意见MOS值达到4．2。在可懂度和清晰度等性能优异,该系统设计可应用于无线移动网、数字多路复用系统和计算机通信系统。     

基于DTW算法语音识别系统的仿真及DSP实现

DTW（DynamicTimeWarping）算法的实现简单有效,在孤立词语音识别系统中得到了广泛的应用。采用谱减法进行前端去噪处理,利用Matlab对语音识别系统进行了仿真,并设计了一种以16位数字信号处理器TMS320VC5509为核心的孤立词语音识别系统。实验结果表明,系统能满足实时性能要求,识别效果良好。     

导引头多源信息AGC系统设计

针对雷达导引头AGC控制处理中传统低通滤波法在输入信号饱和时无法正常工作以及不能直接反映信号幅度的缺陷,通过分析信号幅度与饱和度及功率检波的相互关系,分别提出了基于饱和度的幅度估计方法和平方和功率检波的幅度估计方法,利用这两种方法的特点结合弹载处理机应用,设计了导引头多源信息自动增益控制算法,并给出了实现流程.利用Matlab仿真引入算例,证明其具有响应时间短、控制精度高、系统性能稳定的特点.     

基于凌阳SPCE061A单片机的语音识别系统设计

本文以凌阳公司生产的16位单片机SPCE061A为核心处理器,利用其适用于数字语音识别的特点,设计了一套基于线性预测倒谱和动态时间规整技术(DTW)的特定人孤立词语音识别系统,对系统的硬件电路和软件设计进行了分析.该系统能进行语音指令的识别并作出相应的应答.该系统可以应用在一些智能控制领域,能够大大改善人机交互界面.经检验,指令识别的准确率达到80%.该系统结构简单,具有很高的性价比,便于推广和应用.     

Enhancement of noise-suppressed speech by spectral processing implemented in a digital signal processor

This paper presents a noisy suppressed speech enhancement method by combining the basic spectral subtraction technique and spectral processing in the frequency domain to provide better noise suppression as well as better enhancement in the speech regions. In contrast to several previous approaches we do not try to achieve a complete removal of the noise, but instead our goal is to preserve a pre-defined amount of the original noise in the processed signal. This is accomplished by exploiting the masking properties of the human auditory system. The proposed algorithm is named PM “Proposed Method” which simulates properties of the human auditory system and applies it to the speech recognition system to enhance its robustness. The performance of the speech enhancement algorithm using the proposed masking model was compared with three other speech enhancement methods over 4 different noise types and five SNRs. The performances of the proposed approach are objectively and subjectively compared to the conventional approaches to highlight the aforementioned improvement. In this paper we discuss the design and development of a digital signal processor (DSP) implementation to achieve real-time performance of our filter. The target processor is a Texas Instruments TMS320C6713 floating point DSP.     

基于数字信号处理的集成光学陀螺信号检测方法

集成光学陀螺的输出信号叠加了多种噪声成分,干扰了有用信息的检测.根据集成光学陀螺输出信号的特点,提出了一种在高速数字信号处理器组成的数字系统中,利用数字滤波器及互相关理论,对集成光学陀螺的含噪声信号进行处理的方法.结果表明在信噪比为10 dB的情况下,该技术可以将信号误差基本控制在3%以下,实现了复杂噪声环境下集成光学陀螺系统信号的检测.