Jaya Jeevagan

Sathyabama Institute of Science and Technology

Papers

Total Citations

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About

Jaya Jeevagan is a researcher whose work sits at the intersection of artificial intelligence, human-computer interaction, and affective computing. Their primary focus is on developing intelligent systems capable of interpreting and responding to human emotional states, with a particular emphasis on audio signal processing. Jeevagan’s most cited work, "Human Emotion Recognition by Audio Signals using MLP Classifier" (2023), has garnered 8 citations and demonstrates a pioneering approach to speech emotion recognition. This research explores how multi-layer perceptron (MLP) classifiers can decode emotional cues from vocal patterns, addressing a critical gap in human-computer interaction. By enabling machines to understand emotions from speech, Jeevagan’s contributions have practical implications for diverse applications—from more empathetic customer service in banking and contact centers to safer, more intuitive interfaces in automotive dashboards and robotic communication. Their work stands out for bridging technical machine learning methods with real-world usability challenges, making emotional AI more accessible and reliable. Jeevagan’s research continues to shape how we build responsive, human-aware technologies, marking them as a notable voice in the evolving field of affective computing.