Matthias Schultalbers

Ingenieurgesellschaft Auto und Verkehr (Germany)

Papers

Total Citations

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About

Matthias Schultalbers is a robotics researcher whose work centers on human-robot interaction, with a particular focus on making service robots more accessible through natural speech interfaces. His most cited work, "Speech recognition system for a service robot - a performance evaluation" (2020, 12 citations), stands as a foundational contribution to the field of autonomous robotic assistants. In this study, Schultalbers systematically evaluated five automatic speech recognition (ASR) solutions for use as a human-machine interface (HMI) on a service robot, comparing on-device systems—Kaldi's DNN-HMM architecture and Mozilla's end-to-end DeepSpeech—against three cloud-based APIs from IBM Watson, Microsoft Azure, and Google Speech. This comprehensive benchmarking provided critical insights into the trade-offs between latency, accuracy, and computational efficiency for real-world robotic applications. By bridging the gap between state-of-the-art ASR technology and practical robotic deployment, Schultalbers has helped pave the way for more intuitive, voice-controlled service robots that can operate effectively in dynamic environments. His work continues to influence researchers developing accessible, speech-driven interfaces for autonomous systems.