Arabic Speech Recognition for Industrial Commands: A Review
Naouar Laaidi, Abderrahim Ezzine, Mohamed Lamrini, Hassan Satori · 2024
The integration of speech recognition technology in industrial environments has significantly enhanced humanmachine interaction, offering hands-free control over machinery in complex and noisy settings. This review focuses on the application of speech recognition for industrial command systems, with a particular emphasis on stochastic approaches such as Hidden Markov Models and their extensions. We examine the challenges posed by noisy environments, linguistic variability, and dialectal diversity, especially in Arabic, as well as the opportunities offered by advanced methods like deep learning. The paper also highlights emerging hybrid models that combine traditional and modern techniques to improve accuracy and robustness. Finally, the review outlines future research directions for optimizing speech recognition in industrial settings.