Norelhouda Azzizi

University Frères Mentouri Constantine 1

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About

Norelhouda Azzizi is a researcher in artificial intelligence and speech recognition, with a focused expertise in neural network architectures for voice-controlled systems. Her work centers on optimizing the learning processes of Multi-Layer Perceptron (MLP) neural networks for speech and command recognition. Azzizi’s key contributions include pioneering studies on the minimal training elements required for effective neural network learning, particularly in the context of generating robot commands through voice interfaces. Her research, such as "A Learning Process of Multilayer Perceptron for Speech Recognition" and "Design Experiments for Voice Commands Using Neural Networks," has garnered attention for its practical approach to improving artificial system performance through experience-based learning. By analyzing the efficiency of MLP-NN in word recognition and command execution, Azzizi has advanced the understanding of how neural networks can be streamlined for real-world applications. Her work is particularly notable for bridging theoretical learning principles with applied robotics, offering insights into reducing computational overhead while maintaining accuracy. With citations reflecting the foundational nature of her studies, Azzizi’s research continues to influence the development of more efficient, responsive voice-activated systems in human-robot interaction.