Fitrilina
Papers
1
Total Citations
5
H-Index
1
About
Fitrilina is a researcher whose work bridges speech processing, image recognition, and robotics, with a focus on human-machine interaction. Her most cited paper, "Pengenalan Ucapan Metoda MFCC-HMM Untuk Perintah Gerak Robot Mobil Penjejak Identifikasi Warna" (2013, 5 citations), demonstrates a pioneering integration of audio and visual technologies. In this study, she implemented Mel-Frequency Cepstral Coefficients (MFCC) combined with Hidden Markov Models (HMM) for speech recognition, enabling a mobile robot to follow color-based identification commands. This work highlights her contribution to developing intuitive control systems that allow robots to understand spoken instructions while visually tracking targets. Although her citation count is modest, Fitrilina’s research is notable for its practical application in robotics, addressing the growing demand for seamless human-machine interfaces. Her approach combines two critical fields—speech processing and image processing—to create more responsive and autonomous systems. For students and researchers exploring the intersection of audio-visual recognition and robotics, Fitrilina’s work offers a foundational example of how to integrate these technologies for real-world command-and-control tasks.
Research Focus
Key Achievements
Top Papers
- 1