Imane Araf

Moroccan Foundation for Advanced Science, Innovation and Research

Papers

Total Citations

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About

Imane Araf is a researcher at the intersection of artificial intelligence, human-robot interaction, and natural language processing, with a particular focus on speech recognition for assistive robotics. Her most cited work, "Which French speech recognition system for assistant robots?" (2022, 6 citations), addresses a critical yet underexplored challenge: the practical evaluation and selection of French-language speech recognition systems for real-world robotic applications. Rather than developing a new system from scratch, Araf’s contribution lies in systematically comparing existing commercial and open-source speech recognition technologies to determine which is most effective for assistant robots operating in French-speaking environments. This work provides a valuable benchmark for researchers and engineers building voice-controlled assistive robots, saving time and guiding system selection. While early in her career, Araf’s research is significant for bridging the gap between advanced speech recognition capabilities and their deployment in accessible, user-friendly robotic assistants. Her focus on French-language systems also addresses a notable gap in the predominantly English-centric speech recognition literature, making her work especially relevant for Francophone robotics and assistive technology communities.