About
Adam Wynn is a PhD student in the Department of Computer Science at Durham University. He completed an integrated Masters degree in Computer Science from Durham University in 2022. He is interested in AI in education, automatic feedback, adaptive learning and educational technology. Adam's research is currently focused on using technology to enhance the learning experience and aims to develop systems that provide personalised feedback and support to students in real-time.
Research
My research explores the intersection of AI and education. Current projects include multilingual speech emotion recognition, confidence classification from voice, speech synthesis and style transfer, and automatic feedback systems.
Featured Publication
Abstract: Understanding speaker confidence is crucial in educational settings, as it can enhance personalised feedback and improve learning outcomes. This study introduces a novel framework for detecting speaker confidence by integrating human-engineered features with embeddings from the Whisper encoder. To address data limitations, a pseudo-labelling technique is employed to expand the labelled dataset, allowing the model to learn from both human-annotated and model-generated labels. The framework combines traditional speech features including pitch, volume, rate of speech, and the presence of disfluencies and stress, with Whisper embeddings, and uses a co-attention mechanism to fuse these representations and achieve an overall accuracy of 75%. This study contributes to advancing speech analysis, enabling applications that support person-alised learning and speaking skill development.
All Publications
This list is semi-automatically generated and is correct to the best of my knowledge.
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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.