Hamza Attoui
Papers
1
Total Citations
11
H-Index
1
About
Hamza Attoui is a researcher whose work sits at the intersection of robotics, control systems, and speech recognition. His primary research focus is on developing intelligent, voice-driven interfaces for robotic manipulation, aiming to make complex machinery more accessible and intuitive to control. Attoui’s most notable contribution is his work on a Hidden Markov Model/Gaussian Mixture Model (HMM/GMM) based voice command system, designed to improve the control of the remotely operated robot arm TR45. This system, detailed in a 2011 paper with 11 citations, applies robust HMM and GMM for spotted word recognition, using Cepstral coefficients with energy and differentials as features. By integrating speech recognition directly into a tele-manipulator command chain, Attoui’s work demonstrates a practical path toward hands-free, efficient control of industrial and didactic robotic arms. His research is valuable for students and engineers exploring human-robot interaction, offering a concrete example of how machine learning techniques can bridge the gap between human speech and precise mechanical action.
Research Focus
Key Achievements
Top Papers
- 1