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About

Timo Baumann is a researcher whose work sits at the intersection of automatic speech recognition (ASR), human-robot interaction, and socially aware robotics. His key contributions focus on making robots more natural and effective communicators, particularly in real-world, unscripted settings. Baumann’s most cited work, “Improving Domain-independent Cloud-Based Speech Recognition with Domain-Dependent Phonetic Post-Processing” (45 citations), addresses a critical bottleneck in ASR: adapting generic cloud-based systems to specialized domains without costly retraining. This pragmatic approach has helped bridge the gap between commercial speech services and research needs. He is also the lead developer of the SMOOTH-Robot (16 citations), a modular, low-cost service robot designed for versatility across domains, demonstrated through real-world use cases. In human-robot interaction, Baumann explores how robots can initiate conversations naturally—using incremental speech adaptation to adjust volume based on distance (6 citations) and employing polite apologies when intruding on personal space (3 citations). These studies, conducted in-the-wild rather than in labs, highlight his commitment to ecologically valid research. Baumann’s work is notable for its focus on incremental, adaptive speech production, making robots not just functional but socially graceful interaction partners.