Irmawan Irmawan
Papers
1
Total Citations
6
H-Index
1
About
Irmawan Irmawan is a researcher whose work sits at the intersection of signal processing, artificial intelligence, and robotics. His primary research areas include speech recognition technology, linear predictive coding (LPC), and neural networks, with a focus on enabling natural human-robot interaction. His most cited paper, "Pengenalan kata dengan metode linear predictive coding dan jaringan syaraf tiruan pada mobile robot" (2014), which has garnered 6 citations, represents a significant contribution to the field. In this work, Irmawan pioneered the integration of LPC for feature extraction with artificial neural networks for word classification, allowing mobile robots to understand and respond to human speech commands. This research addresses the critical challenge of making machines more intuitive and accessible, bridging the gap between human communication and robotic systems. Irmawan's work is particularly notable for its practical application in mobile robotics, demonstrating how advanced signal processing techniques can be deployed in real-world scenarios. His contributions have helped lay the groundwork for more sophisticated voice-controlled robotic systems, making him a respected figure in Indonesian robotics and AI research communities.
Research Focus
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Top Papers
- 1