activity
20222026
most citedA Framework for Adapting Human-Robot Interaction to Diverse User Groups

4 citations · 9 across the 8 of their papers we have counts for

collaborators

8 papers

cs.CL2026

MoDiCoL: A Modular Diagnostic Continual Learning Dataset for Robust Speech Recognition

Theresa Pekarek Rosin, Matthias Kerzel, Stefan Wermter

Modern Automatic Speech Recognition (ASR) systems have made remarkable progress on standard benchmarks, yet performance gaps have emerged under real-world distribution shifts, caus…

cs.CL2026

Learning to Hear Hesitation: Continual Learning for Disfluency-Aware ASR

Henri-Leon Kordt, Theresa Pekarek Rosin, Jae Hee Lee +1

Despite advances in large-scale Automatic Speech Recognition (ASR), disfluent speech remains challenging, as state-of-the-art systems are often optimized to omit disfluencies, lead…

cs.RO2025

Talking to Robots: A Practical Examination of Speech Foundation Models for HRI Applications

Theresa Pekarek Rosin, Julia Gachot, Henri-Leon Kordt +2

Automatic Speech Recognition (ASR) systems in real-world settings need to handle imperfect audio, often degraded by hardware limitations or environmental noise, while accommodating…

cs.CL2025

Large Language Model Data Generation for Enhanced Intent Recognition in German Speech

Theresa Pekarek Rosin, Burak Can Kaplan, Stefan Wermter

Intent recognition (IR) for speech commands is essential for artificial intelligence (AI) assistant systems; however, most existing approaches are limited to short commands and are…

cs.RO2024★ 4 cited

A Framework for Adapting Human-Robot Interaction to Diverse User Groups

Theresa Pekarek Rosin, Vanessa Hassouna, Xiaowen Sun +4

To facilitate natural and intuitive interactions with diverse user groups in real-world settings, social robots must be capable of addressing the varying requirements and expectati…

cs.CL2023★ 1 cited

Bring the Noise: Introducing Noise Robustness to Pretrained Automatic Speech Recognition

Patrick Eickhoff, Matthias Möller, Theresa Pekarek Rosin +2

In recent research, in the domain of speech processing, large End-to-End (E2E) systems for Automatic Speech Recognition (ASR) have reported state-of-the-art performance on various…