Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review

Yihan Luo

doi:10.47297/taposatWSP2633-456916.20250605

PDF
Export
Share
Collection
Album

Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review

Volume 6, Issue 5

Views: 0 Downloads: 0

Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review
Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review
Southern Methodist University, Dallas, 75207, United States
Vol. 6, Issue 5, Pages: 74-79(2025)
Published：19 May 2025
DOI：10.47297/taposatWSP2633-456916.20250605
Accepted：

Scan QR Code

Luo Yihan.Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review[J].Theory and Practice of Science and Technology,2025,06(05):74-79.
DOI：

Luo Yihan.Enhancing Immersion in Virtual Reality through Embodied Conversational Agents and Machine Learning: A Literature Review[J].Theory and Practice of Science and Technology,2025,06(05):74-79. DOI： 10.47297/taposatWSP2633-456916.20250605.

摘要

Abstract

Virtual Reality (VR) has revolutionized digital interaction by providing immersive environments that simulate real-world experiences. A critical component of successful VR applications is the user's sense of immersion

which encompasses presence

engagement

and realism. This literature review explores the integration of Embodied Conversational Agents (ECAs) and Machine Learning (ML) techniques in enhancing immersion within VR environments. By analyzing current research

this paper highlights key advancements

existing challenges

and potential future directions in this interdisciplinary domain. Particular attention is paid to the role of multimodal interaction

affective computing

and real-time adaptive learning

providing a comprehensive view of this rapidly evolving field.

关键词

Keywords

references

Beale, R., & Creed, C. (2009). Affective interaction: How emotional agents affect users. International Journal of Human-Computer Studies, 67(9), 755-776.

de Melo, C. M., Carnevale, P., & Gratch, J. (2014). The effect of expression of anger and happiness in computer agents on negotiations with humans. Autonomous Agents and Multi-Agent Systems, 30(1), 1-25.

Pfeiffer, T., Latoschik, M. E., & Wachsmuth, I. (2014). Evaluation of multimodal interfaces for virtual environments. Virtual Reality, 18(2), 101-115.

Slater, M., & Wilbur, S. (1997). A framework for immersive virtual environments (FIVE): Speculations on the role of presence in virtual environments. Presence: Teleoperators and Virtual Environments, 6(6), 603-616.

Wang, Q., Wu, H., & Liu, J. (2021). Intelligent tutoring systems with emotion recognition: A systematic review. Educational Technology Research and Development, 69(2), 879-905.

Stanney, K. M., Hale, K. S., Nahmens, I., & Kennedy, R. S. (2003). What to expect from immersive virtual environment exposure: Influences of gender, body mass index, and past experience. Human Factors, 45(3), 504-520.

Bailenson, J. N., Blascovich, J., Beall, A. C., & Loomis, J. M. (2003). Interpersonal distance in immersive virtual environments. Personality and Social Psychology Bulletin, 29(7), 819-833.

Rizzo, A. S., & Koenig, S. T. (2017). Is clinical virtual reality ready for primetime? Neuropsychology, 31(8), 877-899.

Bailenson, J. (2018). Experience on demand: What virtual reality is, how it works, and what it can do. W. W. Norton & Company.

Zhao, J., & Fessler, J. A. (2020). Federated learning with adaptive feature compression for virtual reality applications. IEEE Transactions on Multimedia, 23, 3041-3055.

Kiran, B. R., Sobh, I., Talpaert, V., Mannion, P., Al Sallab, A., Yogamani, S., & Perez, P. (2021). Deep reinforcement learning for autonomous driving: A survey. IEEE Transactions on Intelligent Transportation Systems, 23(7), 4909-4926.

Liu, Y., & Matwin, S. (2019). Multimodal sentiment analysis: From words to speech and facial expressions. Information Fusion, 49, 1-12.

Huynh, D. Q., & Nguyen, D. T. (2020). Eye tracking in virtual reality: A review of challenges and opportunities. Frontiers in Virtual Reality, 1, 12.

Kellnhofer, P., Matusik, W., & Pfister, H. (2019). Real-time gaze estimation using a consumer-grade VR headset. ACM Transactions on Graphics, 38(4), 1-10.

Sra, M., Garrido-Jurado, S., & Schmandt, C. (2016). Procedurally generated virtual reality from 3D reconstruction. Proceedings of the 2016 CHI Conference on Human Factors in Computing Systems, 3576-3587.

Madary, M., & Metzinger, T. K. (2016). Real virtuality: A code of ethical conduct. Recommendations for good scientific practice and the consumers of VR technology. Frontiers in Robotics and AI, 3, 3.

Meta Reality Labs. (2021). Social presence in virtual reality: Advancements and applications. Meta Research Report.

MIT Media Lab. (2020). Reinforcement learning for adaptive embodied conversational agents. MIT Technical Reports.

Stanford Virtual Human Interaction Lab. (2021). Empathy at scale: VR applications for social good. Stanford Reports in Virtual Reality.

IEEE Virtual Reality Community. (2023). Standardizing presence measurement in immersive virtual environments. IEEE VR White Paper.

Alert me when the article has been cited

Submit

Autonomous Agricultural Robots: A Study on Machine Learning and Navigation Algorithms

IVA: A Review of the State-of-the-Art

Evaluation of China's College Financial Aid Based on Personal Data and Credit Score Card Model

Literature Review of Visualizing and Detecting Malware

Empirical Advancements in Convolutional Neural Networks for Image Recognition: A Comparative Analysis

Related Author

Rongguang Sun Zhongkai university of agriculture and engineering

Weiwei Chen Shanghai lixin university of accounting and finance, Information office;Arts et Métiers institute of technology, Laboratory of Fluid and Energy Systems Engineering,151, boulevard de l'hôpital

Xinyue Xu School of Computer Science and Technology, Jilin University

Zhaoheng Yin

Hejun Yang

Pei Gan

Yang Sun

Han Xie

Related Institution

Zhongkai university of agriculture and engineering

Shanghai lixin university of accounting and finance, Information office

Arts et Métiers institute of technology, Laboratory of Fluid and Energy Systems Engineering,151, boulevard de l'hôpital

School of Computer Science and Technology, Jilin University

School of Electrical Engineering and Computer Science, University of Ottawa,, ON

⁰