collaborators

10 papers

cs.CL2026

Speech-to-SOAP: End-to-End Summarization of Medical Dialogues: KIT@BeTraC 2026

Enes Yavuz Ugan, Fabian Retkowski, Yuka Ko +4

With the advent of Large Language Models and its instruction following capabilities a promising application is the task of summarization. Within this domain of task the extractive…

cs.CL2026

The Role of Disfluencies in Speech Translation

Maike Züfle, Maria Teleki, Fabian Retkowski +5

Current speech translation systems, including SpeechLLMs, are trained on cleaned text and tend to strip disfluencies like filled pauses and false starts rather than translate them.…

cs.CL2026

Automatic Labelling of Speech Translation Errors

Dominik Macháček, Maike Züfle, Ondrej Klejch

Errors in speech translations reduce trustworthiness of Speech Translation (ST) systems and can have serious consequences. Yet currently there is no established methodology for eva…

cs.CL2026

Multilingual Long-Form Speech Instruction Following: KIT's Submission to IWSLT 2026

Enes Yavuz Ugan, Maike Züfle, Yuka Ko +5

With the advent of Large Language Models, single-task and token-based multi-task models have evolved into instruction-based systems that infer task and target language implicitly f…

cs.SD2026

Beyond Transcripts: A Renewed Perspective on Audio Chaptering

Fabian Retkowski, Maike Züfle, Thai Binh Nguyen +2

Audio chaptering, the task of segmenting long-form audio into coherent sections, is increasingly important for navigating podcasts, lectures, and videos. Despite its relevance, res…

cs.CL2026

When Helpful Context Leaks: Privacy Risks in Domain-Adapted ASR

Maike Züfle, Jan Niehues

SpeechLLMs are increasingly deployed in professional settings where domain customisation is standard practice: users supply context in prompts with sensitive information, fine-tune…