Causal Structures of Multidimensional QoE in Haptic-Audiovisual Communications: Bayesian Modeling
Causal Structures of Multidimensional QoE in Haptic-Audiovisual Communications: Bayesian Modeling
复制标题
触觉视听通信中多维 QoE 的因果结构：贝叶斯建模
DOI：
10.1145/3375922
复制
发表时间：
2020
期刊：
影响因子：
--
通讯作者：
Shuji Tasaka
中科院分区：
文献类型：
--
作者：
芝山直喜;五十嵐保隆;金子敏信;後田寛紀，西山英輔，豊田一彦;Shuji Tasaka
本文提出了一种方法，用于建立和验证合理的模型，可以表达在多维QoE的触觉视听交互式通信的因果关系。对于建模，我们利用主观实验数据的五点分数收集在以前的研究中，一对受试者进行两种互动的任务（响板击中和对象运动）在真实的空间（而不是在虚拟空间）。多维QoE由响板击中的15个度量和对象移动的14个度量组成。为了降低维度，我们将QoE指标分为三组，作为三个结构（潜在变量或因素）的指标：AVQ（视听质量），HQ（触觉质量）和UXQ（用户体验质量）。然后我们建立两个模型：（1）结构方程模型，其中AVQ和HQ相互关联，对UXQ产生因果效应;（2）验证性因素分析模型，其中三个结构仅相互关联。我们将前者称为3C-SEM，后者称为3C-CFA。我们进一步介绍了一个CFA模型与一个单一的结构，所有的QoE措施是它的指标（1C-CFA）。我们通过马尔可夫链蒙特卡罗模拟的三个模型进行贝叶斯分析，在每个模型中，偏差信息准则的模型比较，后验预测值的计算模型检验。因此，我们发现3C-SEM是最合理的，HQ比AVQ对UXQ有更强的因果关系。我们还了解到，AVQ和UXQ之间的相关性远远高于直接因果效应，相关性的增加是由于HQ通过AVQ与HQ的相关性对UXQ的因果效应。因此，建议改进触觉性能比改进视听性能更有效地增强QoE。
This article proposes a methodology for building and verifying plausible models that can express causation in multidimensional QoE for haptic-audiovisual interactive communications. For the modeling, we utilize subjective experimental data of five-point scores collected in a previous study where a pair of subjects carry out two kinds of interactive tasks (castanets hitting and object movement) in real space (not in virtual space). The multidimensional QoE is composed of 15 measures for the castanets hitting and 14 measures for the object movement. To reduce the dimension, we classify the QoE measures into three groups as indicators of three constructs (latent variables or factors): AVQ (AudioVisual Quality), HQ (Haptic Quality), and UXQ (User eXperience Quality). We then build two models: (1) a structural equation model in which AVQ and HQ correlated with each other give causal effects on UXQ, and (2) a confirmatory factor analysis model in which the three constructs are only correlated with each other. We refer to the former as 3C-SEM and the latter as 3C-CFA. We further introduce a CFA model with a single construct for which all QoE measures are its indicators (1C-CFA). We perform Bayesian analysis of the three models by means of Markov chain Monte Carlo simulation; in each model, the deviance information criterion is obtained for model comparison, and the posterior predictivep-value is calculated for model checking. As a result, we find that 3C-SEM is the most plausible and that HQ has a stronger causal effect on UXQ than AVQ. We also learn that the correlation between AVQ and UXQ is much higher than the direct causal effect and that the increase in the association as correlation is due to the causal effect of HQ on UXQ through the correlation of AVQ with HQ. Thus, it is suggested that improving haptic performance is more effective in enhancement of QoE than improving audiovisual performance.