基于语音质量预测的VoIP自适应抖动缓冲算法

抖动缓冲是解决VoIP系统延时抖动问题的有效方法。为实现抖动缓冲的动态调整,获得更好的VoIP通话质量,提出了一种基于语音质量预测的自适应抖动缓冲算法。算法采用Pareto分布为延时建模,通过E-Model方法预测突发丢包模式下的瞬时语音质量,以最大化语音质量为目标,自适应选择出最优的抖动缓冲区大小。实验仿真结果表明,所提算法明显优于已有算法,能够有效提高VoIP系统的语音质量。     

基于网络性能的VoIP语音质量评价模型

在VoIP应用中,为了实现服务质量的监测和路径切换,通常需要测量路径的网络性能,并将网络性能映射到语音质量评价.本文提出一种基于网络性能的VoIP语音质量评价模型,该模型在E-Model的基础上进行了改进,只考虑网络性能的动态变化对语音质量的影响.新的模型考虑更少的影响因素,比E-Model更容易计算,因此更适用于VoIP系统的语音质量评价.通过实验比较了新的模型和简单的网络参数评价模型,结果显示该模型具有更好的语音质量描述能力.     

一种VoIP语音质量评价模型

在VoIP系统中,传输网络性能(QoS)参数对可感知语音质量(Quality of Experience, QoE)起着基础性的影响作用,但QoS取值情况并不能直接反映和代表QoE水平。为此,基于对VoIP传输特征的分析,首先采用PESQ,E-Model算法分析了单个QoS参数对QoE损伤的影响;在单个因素计算的基础上,通过对E-Model算法的扩展研究了QoS参数综合作用情况下语音QoE值的变化情况;采用回归分析的方法建立了QoS参数与语音 QoE的映射模型,模型构成简单。验证实验表明,该模型与语音QoE客观评价方法之间具有很高的相关度,满足对网络运行状况及VoIP QoE实时监测的要求。     

IEEE802.11e无线局域网语音性能分析模型

无线多媒体传输中,正确评估IEEE802.11e无线局域网的语音质量尤为重要.提出一种IEEE802.11e无线局域网的语音质量评价模型.该模型引入E-Model VoIP语音质量评估方法,估计IEEE802.11e无线局域网的语音质量.重点考虑碰撞丢失对语音质量的影响,建立新的碰撞概率表达式.通过MATLAB、NS2仿真分析比较了不同碰撞概率在新模型下的语音质量.结果表明提出的碰撞概率在新模型下语音质量最接近真实值,具有最高的评估准确度.     

在区分服务上的VoIP仿真评价研究

分析了区分服务的工作原理和影响VoIP语音质量的主要因素,介绍了一种语音质量的客观评价方法——E模型,运用ns-2仿真器构建网络仿真模型,比较VoIP在区分服务和传统网络中的性能表现,利用E模型对VoIP的性能进行了定量的客观评价,并为区分服务对VoIP的支持能力提供了用户级语音质量的分析。     

Vo IP 的语音质量分析与控制

分析了VoIP语音质量的影响因素，通过E模型定量地描述了语音质量与端到端延迟和丢包率的关系。为了控制VoIP的语音质量，计算出VolP系统在各种情况下的语音质量极限，提出一种自适应编码和分组封装的控制策略。将该方法应用于自行开发的IP电话网关，实际测试证明能在很大程度上提高VoIP的语音质量。     

基于语音质量预测的Speex自适应码率控制算法

为实现IP语音(VoIP)质量的动态管理与控制,提出了一种基于语音质量预测的自适应码率控制算法。通过实时预测VoIP通话的瞬时语音质量和总体语音质量,自适应地调整Speex编码参数,从而根据需要选择最佳编码速率。实验仿真结果表明,提出的算法能够有效减少网络拥塞,提高VoIP系统的语音质量。     

基于改进的SOM网络模型的VoIP QoS应用研究

VoIP的服务质量（QoS,Quality of Service）评估可以采用一系列可度量的参数来描述：业务可用性、吞吐量、延迟、抖动、分组丢失率等。现有的感知语音质量评价（PESQ）很难对不同环境下的网络结构进行实时和恰当的语音等级质量分类。为了能够综合考虑几种QoS相关因素,在给出改进的自组织映射神经网络模型（ESOMNN）的基础上,利用ESOM能够对高维输入数据有效分类的特点,提出了将端到端延迟、丢包率、抖动、语音编码以及测试系统标识作为ESOMNN的输入数据,在对采样数据进行训练后可自动完成语音质量评价和映射,并能根据得到的实时变量有效地评价包含多种相关因素的QoS级别。     

提高VoIP语音通信质量方法的研究

探讨了VoIP的关键技术,分析了影响VoIP语音通信质量的因素,提出了提高VoIP语言通信质量的方法,即:优化网络环境、选择合适的编解码、服务质量保障(QoS)、使用颤音缓存。该方法对提高VoIP语音通信质量,推动VoIP业务的普及具有实际意义。     

E模型基于延迟抖动的扩展

抖动是影响VOIP语音质量的主要因素之一,它的影响主要表现在导致延迟状态不稳定及使丢包率增加两方面,使用PESQ方法可以定量地分析抖动在这两方面对语音质量造成的影响.在此基础上对E模型进行扩展,为E模型加入抖动这个参数,从而更准确地预测质量.实验结果表明,与原模型相比,在延迟不稳定的情景下它比原模型更加准确.     

基于E-Model的语音帧分组传输性能研究

voIP的语音帧分组大小是实时语音传输的关键参数。为提高网络效率和最大话路数,采用EModel的方法分析了RTP包中语音帧个数、语音长度、丢包概率和抖动缓冲区大小对语音质量的影响,给出了不同带宽时的最佳传输分组大小。仿真结果表明,在保证最基本的话音质量情况下,为不同链路确定合适的分组语音帧数能有效提高链路的最大话路数。     

Evaluating perceived voice quality on packet networks using different random neural network architectures

Voice over Internet Protocol (VoIP) is one of the fastest growing technologies in the world. In VoIP speech signals are transmitted over the same network used for data communications. The internet is not a robust network and is subjected to delay, jitter, and packet loss. It is very important to measure and monitor the quality of service (QoS) the users experience in VoIP networks; this is not an easy task and usually requires subjective tests. In this paper we have analyzed three non-intrusive models to measure and monitor voice quality using Random Neural Networks (RNN). A RNN is an open queuing network with positive and negative signals. We have assessed the voice quality based on various parameters i.e. delay, jitter, packet loss, and codec. In our approach we have used the Mean Opinion Score (MOS) calculated using a Perceptual Evaluation of Speech Quality (PESQ) algorithm to generate data for training the RNN model. We have studied two feed-forward models and a recurrent architecture. We have found that the simple feed-forward architecture has produced the most accurate results compared to the other two architectures.     

基于E-model的VoIP语音质量评估的研究

为准确评估VoIP）语音质量，对E—model算法进行了深入研究，剖析了E—model算法的组成部分Id，Is，Ie，A，探讨了丢包、延迟和抖动对VoIP质量的影响，并应用该算法对多种语音编码进行了评估。实验证明该客观评估算法主观与客观相关度高，有较强的适应性，可靠性，实用性，完全可用于VoIP语音质量评估。     

A Methodology for Deriving VoIP Equipment Impairment Factors for a Mixed NB/WB Context

This paper proposes a novel approach to quantifying the quality degradation of Voice over IP (VoIP) telephony in the presence of codec and network-related impairments. This approach differs from the baisc ITU-T E-Model for VoIP quality estimation in that it addresses mixed narrowband/wideband scenarios. It makes novel use of instrumental models and symbolic regression via Genetic Programming (GP) to enable the evolution of degradation models from a modest set of initial parameters. Here, a two-step approach has been used. First, values of impairment factors are derived using WB-PESQ as a reference model. Secondly, a GP based symbolic regression approach has been utilized to automatically evolve the functional form of equipment impairment factors from a set of variables. Very few a priori assumptions are made about the model structure. The effectiveness of the approach is demonstrated by a number of generated models which compare favorably with WB-PESQ and outperform the traditional E-Model in terms of prediction accuracy when compared using WB-PESQ. A significant advantage of the approach is that new models are easily generated to account for continuing evolution of the VoIP standards.      

Playout buffering of speech packets based on a quality maximization approach

To combat jitter problems in voice streaming over packet networks, playout buffering algorithms are used at the receiver side. Most of the proposed solutions rely on two main operations: prediction of delay statistics for future packets; setting of the end-to-end delay so as to limit or avoid packet losses. In recent years, a new approach has been presented, which is based on using a quality model to evaluate the impact of both packet loss and delay on the voice quality. Such a model is used to find the buffer setting that maximizes the expected quality. In this paper, we present a playout buffering algorithm whose main contribution is the extension of the new quality-based approach to the case of voice communications affected by bursty packet losses. This work is motivated by two main considerations: most of IP telephony applications are characterized by bursty losses instead of random ones; the human perception of the speech quality is significantly affected by the temporal correlation of losses. To this purpose, we make use of the extensions proposed in the ETSI Tiphon for the ITU-T E-Model so as to incorporate the effects of loss burstiness on the perceived quality. The resulting playout algorithm estimates the characteristics of the loss process varying the end-to-end delay, weights the loss and the delay effects on the perceived quality, and maximizes the overall quality to find the optimal setting for the playout buffer. The experimental results prove the effectiveness of the proposed technique.     

基于抖动激励的VoIP终端拥塞控制机制

针对基于H．323的VoIP系统，提出了一种抖动激励式终端拥塞控制机制，将语音分组的延迟抖动参数与RTCP协议相结合，控制动态改变语音编码方式及传输分组大小，从而缓解网络拥塞，降低传输延时和丢包率。     

A Garch-based adaptive playout delay algorithm for VoIP

Network delay, packet loss and network delay variability (jitter) are important factors that impact on perceived voice quality in VoIP networks. An adaptive playout buffer is used in a VoIP terminal to overcome jitter. Such a buffer-control must operate a trade-off between the buffer-induced delay and any additional packet loss rate. In this paper, a Garch-based adaptive playout algorithm is proposed which is capable of operating in both inter-talkspurt and intra-talkspurt modes. The proposed new model is based on a Garch model approach; an ARMA model is used to model changes in the mean and the variance. In addition, a parameter estimation procedure is proposed, termed Direct Garch whose cost function is designed to implement a desired packet loss rate whilst minimising the probability of consecutive packet losses occurring. Simulations were carried out to evaluate the performance of the proposed algorithm using recorded VoIP traces. The main result is as follows; given a target Packet Loss Rate (PLR) the Direct Garch algorithm produces parameter estimates which result in a PLR closer than other algorithms. In addition, the proposed Direct Garch algorithm offers the best trade-off between additional buffering delay and Packet Loss Rate (PLR) compared with other traditional algorithms.