activity
20242026
most citedThe AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?

2 citations · 3 across the 16 of their papers we have counts for

collaborators

16 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

How to Recognize New Words: A Comparison Between Context Biasing Methods and Speech LLMs

Christian Huber, Alexander Waibel

Recognizing new and rare words - named entities, acronyms, domain specific special words, and other items scarce in training data - remains a key challenge for automatic speech rec…

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

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.CL2026

Adapting Foundation ASR Models to Dysarthric Speech: A Case Study

Christian Huber, Laura Kernahan, Alexander Waibel

Automatic speech recognition (ASR) systems often perform poorly in dysarthric speech, limiting their usefulness to affected speakers in everyday communication. This paper presents…

cs.CL2026

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…

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.CL2025

Paragraph Segmentation Revisited: Towards a Standard Task for Structuring Speech

Fabian Retkowski, Alexander Waibel

Automatic speech transcripts are often delivered as unstructured word streams that impede readability and repurposing. We recast paragraph segmentation as the missing structuring s…

cs.CL2025

BOOM: Beyond Only One Modality KIT's Multimodal Multilingual Lecture Companion

Sai Koneru, Fabian Retkowski, Christian Huber +5

The globalization of education and rapid growth of online learning have made localizing educational content a critical challenge. Lecture materials are inherently multimodal, combi…

cs.CL2025

Context Biasing for Pronunciation-Orthography Mismatch in Automatic Speech Recognition

Christian Huber, Alexander Waibel

Neural sequence-to-sequence systems deliver state-of-the-art performance for automatic speech recognition. When using appropriate modeling units, e.g., byte-pair encoding, these sy…

cs.CL2025★ 2 cited

The AI Co-Ethnographer: How Far Can Automation Take Qualitative Research?

Fabian Retkowski, Andreas Sudmann, Alexander Waibel

Qualitative research often involves labor-intensive processes that are difficult to scale while preserving analytical depth. This paper introduces The AI Co-Ethnographer (AICoE), a…

cs.CL2025

Zero-Shot Strategies for Length-Controllable Summarization

Fabian Retkowski, Alexander Waibel

Large language models (LLMs) struggle with precise length control, particularly in zero-shot settings. We conduct a comprehensive study evaluating LLMs' length control capabilities…

cs.CL2024

Titanic Calling: Low Bandwidth Video Conference from the Titanic Wreck

Fevziye Irem Eyiokur, Christian Huber, Thai-Binh Nguyen +5

In this paper, we report on communication experiments conducted in the summer of 2022 during a deep dive to the wreck of the Titanic. Radio transmission is not possible in deep sea…

eess.AS2024

Handling Numeric Expressions in Automatic Speech Recognition

Christian Huber, Alexander Waibel

This paper addresses the problem of correctly formatting numeric expressions in automatic speech recognition (ASR) transcripts. This is challenging since the expected transcript fo…

cs.CL2024★ 1 cited

From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions

Fabian Retkowski, Alexander Waibel

Text segmentation is a fundamental task in natural language processing, where documents are split into contiguous sections. However, prior research in this area has been constraine…

cs.CL2024

Continuously Learning New Words in Automatic Speech Recognition

Christian Huber, Alexander Waibel

Despite recent advances, Automatic Speech Recognition (ASR) systems are still far from perfect. Typical errors include acronyms, named entities, and domain-specific special words f…