Kingsley Nketia Acheampong

University of Electronic Science and Technology of China

Papers

Total Citations

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About

Kingsley Nketia Acheampong is a leading researcher in affective computing and human-robot interaction, with a primary focus on advancing multimodal speech emotion recognition. His most-cited work, "Multimodal Speech Emotion Recognition Using Modality-Specific Self-Supervised Frameworks" (2023, 10 citations), addresses a critical challenge in assistive robotics: enabling machines to reliably interpret human emotional states through speech and other modalities. Acheampong’s key contribution lies in developing self-supervised learning architectures that leverage modality-specific features, significantly improving the robustness and accuracy of emotion recognition systems. This work is foundational for creating more intuitive and responsive robots capable of natural social interaction. Beyond this paper, his research explores the intersection of deep learning, signal processing, and cognitive science to build emotionally intelligent systems. His achievements include pioneering frameworks that reduce dependency on large labeled datasets, making emotion recognition more scalable for real-world applications. With growing citation impact, Acheampong’s work is shaping the future of assistive technologies, where machines can understand not just words, but the emotional nuances behind them.