Papers by Fabian Retkowski

6 papers
Beyond Transcripts: A Renewed Perspective on Audio Chaptering (2026.acl-long)

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Challenge: despite its relevance, research on audio chaptering remains limited and predominantly textbased . authors: audio chapterers can't be used linearly because they skim, scrub timelines, jump to relevant moments . acoustic features and learning representations are not used for audio chapterer evaluation .
Approach: They propose to use audio-only architecture to automatically segment audio into coherent sections . they compare audio-based models with acoustic features and a novel audio-oriented architecture .
Outcome: The proposed audio-only architecture outperforms text-based approaches on acoustic features and LLMs.
Summarizing Speech: A Comprehensive Survey (2025.emnlp-main)

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Challenge: Podcasts and other audiovisual content are becoming more and more a part of everyday communication and the digital age is changing from text to voice.
Approach: They synthesize the current state of the field and highlight the need for realistic evaluation benchmarks and multilingual datasets.
Outcome: The proposed frameworks are based on evaluation protocols and datasets and highlight the need for realistic benchmarks and multilingual datasets.
From Text Segmentation to Smart Chaptering: A Novel Benchmark for Structuring Video Transcriptions (2024.eacl-long)

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Challenge: Existing benchmarks for text segmentation are small in scale, synthesized, or only contain well-structured documents.
Approach: They propose a benchmark YTSeg focusing on spoken content that is unstructured and unstructures . they also introduce an efficient hierarchical segmentation model MiniSeg that outperforms state-of-the-art benchmarks.
Outcome: The proposed model outperforms state-of-the-art models on unstructured spoken content . the proposed model could be used for "smart chaptering" tasks .
Zero-Shot Strategies for Length-Controllable Summarization (2025.findings-naacl)

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Challenge: Large language models struggle with precise length control, particularly in zero-shot settings.
Approach: They propose to use length approximation, target adjustment, sample filtering and automated revisions to improve LLMs' length control capabilities.
Outcome: The proposed methods improve length control in large language models while maintaining or enhancing summary quality without the need for model fine-tuning or architectural changes.
End-to-End Evaluation for Low-Latency Simultaneous Speech Translation (2023.emnlp-demo)

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Challenge: a framework to evaluate low-latency speech translations is currently only limited to specific aspects and is not able to compare different approaches.
Approach: They propose a framework to perform and evaluate low-latency speech translation in realistic conditions.
Outcome: The proposed framework evaluates various aspects of low-latency speech translation under realistic conditions.
BOOM: Beyond Only One Modality KIT’s Multimodal Multilingual Lecture Companion (2026.eacl-demo)

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Challenge: a multimodal multilingual lecture companion is needed to preserve lecture content in its entirety . globalization of education and rapid growth of online learning have made localizing educational content a challenge .
Approach: They propose a multimodal multilingual lecture companion that translates lecture audio and slides to produce synchronized outputs across three modalities.
Outcome: The proposed solution preserves the original content in its entirety while preserving translations across three modalities.

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