声回波抵消技术的研究

【作者】 魏建强；

【导师】 殷福亮；

【作者基本信息】 大连理工大学 ， 信号与信息处理， 2002， 硕士

【摘要】 随着通讯、数字信号处理和大规模集成电路技术的飞速发展，人们对声音通讯系统(比如视频会议系统等)中的话音质量提出了越来越高的要求。然而，使这些系统能达到令人满意的话音质量并不是一件容易的事情。由于存在从扬声器到麦克风的声音反馈路径，为了得到满意的听音水平，最重要的需求就是应使这些系统具有抗自激和回波信号的能力。因此，回波消除技术也就成为世界各大通讯公司竞争的热点技术之一。 本文主要研究用于声音通讯系统中的声回波抵消技术。声回波抵消通常采用声回波抵消器来实现，最简单的声回波抵消器由自适应滤波器组成。我们可以借助于它宋估计回波信号，并从麦克风信号中减掉该估计值来实现声回波的抵消。 全文共分六章： 第一章简要介绍了有关声回波抵消器的背景知识，包括声回波产生机理，声回波抵消原理及声回波抵消器的基本构成模块。最后，介绍了本论文所做的主要工作。 第二章主要讨论了各种自适应滤波算法。分析了最小均方误差(LMS)算法、归一化的最小均方误差(NLMS)算法和递归的最小二乘(RLS)算法，并且结合声回波抵消算法评估了它们的性能。 为了进一步降低声回波抵消算法的计算复杂性和改善其收敛特性，在第三章中，讨论了各种子带滤波算法，比如DFT子带和FIR子带等。最后，将归一化最小均方误差(NLMS)算法和子带技术相结合，介绍了子带归一化最小均方误差(Subband NLMS)算法。 第四章主要讨论了声回波抵消系统中的各种实现问题，比如双讲检测、有限精度的影响、非线性处理和自激信号的检测与控制。 最后两章给出了具体的实验结果和未来工作展望。其中主要测试指标为回波消去量(ERLE)和收敛速度。更多还原

【Abstract】 With the rapid development of communication techniques, digital signal processing and VLSI techniques, people demand higher and higher speech quality in communication. However, it is not always easy to implement acoustic equipments for communication system with satisfactory speech quality. The most important requirement is to protect against howling and echo, due to acoustic feedback from loudspeaker to microphone, and to ensure a sufficient listening level. So acoustic echo cancellation (AEC) technique has become a hot issue of competition in the famous communication company all over the world.This paper is focused on the AEC in communication system, e.g. videoconference system. Acoustic echo cancellation is normally achieved by means of an acoustic echo canceller, which, in its simplest form, consists of an adaptive filter which estimates the echo signal and subtracts this estimate from the microphone signal.This paper is organized as follows:The background knowledge about AEC such as acoustic echo mechanism, principle of AEC and basic components of AEC is introduced in Chapter 1.In Chapter 2, many kinds of adaptive filter algorithms are discussed. This section analyzes the Least Mean Squares (LMS), Normalized LMS (NLMS) and Recursive Least Squares (RLS) algorithms, and evaluates their performance as acoustic echo canceller.In order to further reduce the computation complexity and improve the convergence behavior, many sorts of subband filter algorithms are depicted in Chapter 3. Finally, associated with NLMS algorithm, the suband NLMS (SNLMS) algorithm is proposed.In Chapter 4, various implementation issues associated with an acoustic echo cancellation system, such as double-talk detection, finite precision effects, nonlinear processing and howling detection and control are discussed.Finally, experiment results are given to demonstrate the performance of the proposed AEC algorithm, where ERLE and rate of convergence are the main indexes.更多还原