Abstract
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 predictive p-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.
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- Judea Pearl. 2009. Causality: Models, Reasoning, and Inference (2nd ed.). Cambridge University Press.Google Scholar
Cross Ref
- Judea Pearl, Madelyn Glymour, and Nicholas P. Jewell. 2016. Causal Inference in Statistics, A Primer. John Wiley 8 Sons.Google Scholar
- Stanley A. Mulaik. 2009. Linear Causal Modeling with Structural Equations. CRC Press, Boca Raton, FL.Google Scholar
- Peter Brooks and Bjørn Hestnes. 2010. User measures of quality of experience: Why being objective and quantitative is important. IEEE Network 24, 2 (March/April 2010), 8--13.Google Scholar
Digital Library
- Khalil ur Rehman Laghari, Noel Crespi, and Kay Connelly. 2012. Toward total quality of experience: A QoE model in a communication ecosystem. IEEE Communications Magazine 50, 4 (Apr. 2012), 58--65.Google Scholar
- Patrick Le Callet, Sebastian Möller, and Andrew Perkis eds. 2013. Qualinet White Paper on Definitions of Quality of Experience, Version 1.2 (2012). European Network on Quality of Experience in Multimedia Systems and Services (COST Action IC 1003), Lausanne, Switzerland.Google Scholar
- Eckehard Steinbach, Sandra Hirche, Marc Ernst, Fernanda Brandi, Rahul Chaudhari, Julius Kammerl, and Iason Vittorias. 2012. Haptic communications. Proceedings of the IEEE 100, 4 (April 2012), 937--956. DOI:10.1109/JPROC.2011.2182100Google Scholar
Cross Ref
- Eiichi Isomura, Shuji Tasaka, and Toshiro Nunome. 2013. QoE enhancement by media adaptive intra-stream synchronization in audiovisual and haptic IP communications. IEICE Transactions on Communications (in Japanese) J96--B, 2 (Feb. 2013), 59--70.Google Scholar
- Kenneth A. Bollen. 1989. Structural Equations with Latent Variables. John Wiley 8 Sons.Google Scholar
- Xin-Yuan Song and Sik-Yum Lee. 2012. Basic and Advanced Bayesian Structural Equation Modeling with Application in the Medical and Behavioral Sciences. John Wiley 8 Sons.Google Scholar
- David Bartholomew, Martin Knott, and Irini Moustaki. 2011. Latent Variable Models and Factor Analysis: A Unified Approach (3rd ed.). John Wiley 8 Sons.Google Scholar
- Rex B. Kline. 2016. Principles and Practice of Structural Equation Modeling (4th ed.). Guilford Press.Google Scholar
- Karl G. Jöreskog and Dag Sörbom. 1993. LISREL 8: Structural Equation Modeling with the SIMPLIS Command Language. Scientific Software International.Google Scholar
- Roy Levy and Robert J. Mislevy. 2016. Bayesian Psychometric Modeling. CRC Press, Boca Raton, FL.Google Scholar
- Peter Congdon. 2006. Bayesian Statistical Modelling (2nd ed.). John Wiley 8 Sons.Google Scholar
- Peter Congdon. 2014. Applied Bayesian Modelling (2nd ed.). John Wiley 8 Sons.Google Scholar
- Shuji Tasaka. 2016. Bayesian structural equation modeling of multidimensional QoE in haptic-audiovisual interactive communications. In Proceedings of the 2016 International Conference on Communications. 3345--3350. DOI:10.1109/ICC.2016.7511202Google Scholar
Cross Ref
- Tatsuya Yamazaki, Masato Eguchi, Takumi Miyoshi, and Kyoko Yamori. 2012. A service quality coordination model bridging QoS and QoE. In Proceedings of the 2012 IEEE 20th International Workshop on Quality of Service (IWQoS’12).Google Scholar
Digital Library
- Shuji Tasaka. 2019. Bayesian categorical modeling of multidimensional QoE in haptic-audiovisual communications. In Proceedings of the 2019 International Conference on Communications. 1--7. DOI:10.1109/ICC.2019.8761784Google Scholar
Cross Ref
- Abdelwahab Hamam, Nicholas D. Georganas, and Abdulmotaleb El Saddik. 2010. Effect of haptics on the Quality of Experience. In Proceedings of the 2010 IEEE International Symposium on Haptic Audio Visual Environments and Games (HAVE’10). 1--6. DOI:10.1109/HAVE.2010.5623992Google Scholar
Cross Ref
- Abdelwahab Hamam, Mohamad Eid, and Abdulmotaleb El Saddik. 2013. Effect of kinesthetic and tactile haptic feedback on quality of experience of edutainment applications. Multimedia Tools and Applications 67, (2013), 455--472. DOI:10.1007/s11042-012-0990-7Google Scholar
Digital Library
- Abdelwahab Hamam, Abdulmotaleb El Saddik, and Jihad Alja’am. 2014. A quality of experience model for haptic virtual environments. ACM Transactions on Multimedia Computing, Communications, and Applications 10, 3 (April 2014), Article 28, 23 pages. DOI:10.1145/2540991.Google Scholar
Digital Library
- Kai Iwata, Yutaka Ishibashi, Norishige Fukushima, and Shinji Sugawara. 2010. QoE assessment in haptic media, sound, and video transmission: Effect of playout buffering control. Computers in Entertainment 8, 2 (Dec. 2010), Article 12. DOI:10.1145/1899687.1899694Google Scholar
Digital Library
- Ayano Tatematsu, Yutaka Ishibashi, Norishige Fukushima, and Shinji Sugawara. 2010. QoE assessment in haptic media, sound, and video transmission: Effect of playout buffering control. In Proc. 2010 IEEE Intern. Workshop Tech. Committee on Commun. Quality Reliability (CQR2010) 6 pages, June 2010. DOI:10.1109/CQR.2010.5619913Google Scholar
Cross Ref
- Eiichi Isomura, Shuji Tasaka, and Toshiro Nunome. 2013. A multidimensional QoE monitoring system for audiovisual and haptic interactive IP communications. In Proceedings of the 2013 IEEE 10th Consumer Communications and Networking Conference (CCNC’13). 196--202.Google Scholar
Cross Ref
- J. Kenneth Salisbury and Mandayam A. Srinivasan. 1997. Phantom-based haptic interaction with virtual objects. IEEE Computer Graphics and Applications 17, 5 (Sept./Oct. 1997), 6--10. DOI:10.1109/MCG.1997.10014Google Scholar
- James L. Arbuckle. 2012. IBM SPSS Amos21 User’s Guide. Amos Development Corporation.Google Scholar
- David Lunn, Christopher Jackson, Nicky Best, Andrew Thomas, and David Spiegelhalter. 2013. The BUGS Book. CRC Press, Boca Raton, FL.Google Scholar
- OpenBUGS. 2015. OpenBUGS License. Retrieved January 27, 2020 from http://www.openbugs.net/w/Downloads.Google Scholar
- Shuji Tasaka. 2017. Bayesian hierarchical regression models for QoE estimation and prediction in audiovisual communications. IEEE Transactions on Multimedia 19, 6 (June 2017), 1195--1208. DOI:10.1109/TMM.2017.2652064Google Scholar
Digital Library
- John C. Loehlin and A. Alexander Beaujen. 2017. Latent Variable Models. Routledge.Google Scholar
- Harry McGurk and John MacDonald. 1976. Hearing lips and seeing voices. Nature 264 (Dec. 1976), 746--748.Google Scholar
- Shuji Tasaka and Yoshihiro Ito. 2003. Psychometric analysis of the mutually compensatory property of multimedia QoS. In Proceedings of the IEEE International Conference on Communications. 1880--1886.Google Scholar
Cross Ref
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Causal Structures of Multidimensional QoE in Haptic-Audiovisual Communications: Bayesian Modeling
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