An Empirical Method for Causal Inference of Constructs for QoE in Haptic-Audiovisual Communications
An Empirical Method for Causal Inference of Constructs for QoE in Haptic-Audiovisual Communications
复制标题
触觉视听通信中 QoE 结构因果推理的经验方法
DOI：
10.1145/3473986
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发表时间：
2022
期刊：
影响因子：
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通讯作者：
Shuji Tasaka
中科院分区：
文献类型：
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作者：
小野滉貴;石井光治;Shuji Tasaka
本文提出了一种实证方法来推断多媒体通信中多维体验质量（QoE）的因果方向，指出QoE的因果关系是感性的。作为建模框架的一个例子，我们选择了一个贝叶斯结构方程模型（SEM），该模型是先前为触觉视听交互通信建立的。SEM包括三个结构（视听质量、触觉质量和用户体验质量），它们是潜在变量，每个潜在变量代表一组具有相似特征的观察变量。在SEM中，利用领域知识假设构念的因果方向。本文旨在提出一种方法，通过单独观察数据验证SEM中因果方向的假设，从而推断构造的因果方向。为此，我们比较了六个具有不同构念因果方向的sem，其中一个是来自领域知识的sem。该方法基于贝叶斯方法和马尔可夫链蒙特卡罗（MCMC）模拟进行QoE预测。将观察得分设置为每个SEM中外生变量的指标，我们预测所有指标的值；然后，我们从观察到的分数中评估预测的QoE和平均意见得分（MOS）之间的均方误差（MSE），并估计MSE在每个SEM中的概率分布。我们可以比较任意两个SEM，通过检查一个SEM的MSE小于或等于另一个SEM的MSE的概率来找到哪个更合理。这些概率是用MCMC模拟估计出来的。该方法表明，由此推断的触觉视听交互通信的因果方向能够充分支持从领域知识中得出的原始因果方向。此外，我们证明了QoE的行为类似于Jay、Glencross和Hubbold在2007年提出的延迟触觉和视觉反馈对协作环境中表现的影响的“影响-感知-适应”模型，并且它伴随着似是而非的因果方向的反转，就像人字拖一样。
This article proposes an empirical method for inferring causal directions in multidimensional Quality of Experience (QoE) in multimedia communications, noting that causation in QoE is perceptual. As an example for modeling framework, we pick up a Bayesian structural equation model (SEM) previously built for haptic audiovisual interactive communications. The SEM includes three constructs (Audiovisual quality, Haptic quality, and User experience quality), which are latent variables each representing a group of observed variables with similar characteristics. In the SEM, the causal directions of the constructs were assumed by resorting to the domain knowledge. This article aims at proposing a methodology for inferring causal directions of constructs in general by verifying the assumption of causal directions in the SEM through their observed data alone. For that purpose, we compare six SEMs each with different causal directions of constructs, one of which is the one from the domain knowledge. The proposed method is based on QoE prediction by a Bayesian approach with Markov chain Monte Carlo (MCMC) simulation. Setting observed scores to the indicators of exogenous variables in each SEM, we predict values of all the indicators; we then assess the mean square error (MSE) between predicted QoE and mean opinion score (MOS) from observed scores and estimate the probability distribution of the MSE in each SEM. We can compare any two SEMs to find which is more plausible by examining the probability that the MSE for one SEM is smaller than or equal to that for the other. These probabilities are estimated with MCMC simulation. The method indicates that the causal directions thus inferred for the haptic audiovisual interactive communications adequately support the original ones drawn from the domain knowledge. In addition, we demonstrate that QoE can behave like the “impact-perceive-adapt” model of the effects of delayed haptic and visual feedback on performance in a collaborative environment, which Jay, Glencross, and Hubbold proposed in 2007, and that it accompanies reversal of plausible causal directions like a flip–flop.