11 citations · 11 across the 9 of their papers we have counts for
13 papers · 1 filter
Controlling Backchannels in Streamable Full-duplex Models
Maike Züfle, Peter Polák, Sefik Emre Eskimez +3
Backchannels, brief acknowledgements like "uh-huh" produced while the other party may still be talking, are central to natural conversation, but full-duplex spoken dialogue models…
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…
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…
F-Actor: Controllable Conversational Behaviour in Full-Duplex Models
Maike Züfle, Ondrej Klejch, Nicholas Sanders +3
Spoken conversational systems require more than accurate speech generation to have human-like conversations: to feel natural and engaging, they must produce conversational behaviou…
Hearing to Translate: The Effectiveness of Speech Modality Integration into LLMs
Sara Papi, Javier Garcia Gilabert, Zachary Hopton +8
As Large Language Models (LLMs) expand beyond text, integrating speech as a native modality has given rise to SpeechLLMs, which directly process spoken language and enable speech-t…
COMET-poly: Machine Translation Metric Grounded in Other Candidates
Maike Züfle, Vilém Zouhar, Tu Anh Dinh +3
Automated metrics for machine translation attempt to replicate human judgment. Unlike humans, who often assess a translation in the context of multiple alternatives, these metrics…