17 papers
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.…
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…
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…
Why We Need Speech to Evaluate Speech Translation
Maike Züfle, Danni Liu, Vilém Zouhar +1
Speech translation models are increasingly capable of preserving speech-specific information (e.g., speaker gender, prosody, and emphasis), yet evaluation metrics remain blind to s…
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…
Do What I Say: A Spoken Prompt Dataset for Instruction-Following
Maike Züfle, Sara Papi, Fabian Retkowski +5
Speech Large Language Models (SLLMs) have rapidly expanded, supporting a wide range of tasks. These models are typically evaluated using text prompts, which may not reflect real-wo…