About
Adam Wynn is a researcher at Durham University, where he recently completed his PhD (passed subject to minor corrections) in the Department of Computer Science as a member of the Artificial Intelligence and Human Systems (AIHS) group, focusing on automatic feedback and personalised support frameworks for speech training. Previously, he completed an integrated Masters degree in Computer Science from Durham University in 2022. He is interested in Applied AI, speech processing, AI in education, AI in health, automatic feedback, adaptive learning, and educational technology.
Research
My research currently focuses on developing intelligent, adaptive learning environments. By combining multimodal speech processing with automated feedback pipelines, I build end-to-end Machine Learning frameworks that interpret complex human inputs to provide real-time, personalised feedback to learners. Current projects include multilingual speech emotion recognition, confidence classification from voice, speech synthesis and style transfer, and automatic feedback systems.
The list below of all publications is semi-automatically generated and is correct to the best of my knowledge.
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[Preprint] A Semi-Supervised Framework for Speech Confidence Detection using Whisper
Wynn, A. & Wang, J. (2026). arXiv preprint arXiv:2605.12387. -
EmoBridge: Bridging Emotion Comprehension from Avatars to Human Faces for Individuals with Autism Spectrum Disorder
Wang, J., Wynn, A., & Wood, R. (2026). ICT4AWE 2026. Best Paper Award. -
Lowering Novice Programming Barriers with MediaLib: Studies of its Effectiveness and Transferability
Wang, J., Wynn, A., Valente, A., Sun, D., & Marchetti, E. (2026). Smart Learning Environments, 13, 25. -
Evaluating Adaptive and Generative AI-Based Feedback and Recommendations in a Knowledge-Graph-Integrated Programming Learning System
Nongkhai, L. N., Wang, J., Wynn, A., & Mendori, T. (2025). Computers and Education: Artificial Intelligence, 100526.