Omar Bourja

Moroccan Foundation for Advanced Science, Innovation and Research

Papers

Total Citations

H-Index

About

Omar Bourja is a researcher advancing the frontiers of human-robot interaction through robust speech recognition technologies. His work focuses on overcoming critical limitations in current automatic speech recognition (ASR) systems, particularly for assistive robotics. Bourja’s key research areas include out-of-vocabulary (OOV) word adaptation, comparative evaluation of ASR architectures, and the deployment of speech interfaces in robotic platforms. His most-cited paper, “Adapting Off-the-Shelf Speech Recognition Systems for Novel Words” (2023, 6 citations), tackles the persistent challenge of recognizing proper nouns and neologisms—words that cause dialog systems to fail. By proposing methods to adapt existing ASR models without retraining from scratch, Bourja offers a practical path toward more resilient voice-controlled robots. His earlier work, “Which French speech recognition system for assistant robots?” (2022, 6 citations), provides a crucial benchmark for developers, systematically comparing commercial and open-source French ASR systems to identify the most effective solution for real-world robotic applications. Though early in his career, Bourja’s contributions are already shaping how robots understand dynamic human speech, directly impacting the reliability of voice interfaces in homes and healthcare settings.