Papers by Lukas Fischer

4 papers
SwissADT: An Audio Description Translation System for Swiss Languages (2025.naacl-industry)

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Challenge: despite advances in multilingual machine translation, lack of well-crafted AD data impedes development of audio description translation systems.
Approach: They propose an audio description translation system for three main Swiss languages and English . they combine human expertise with the power of Large Language Models to improve quality .
Outcome: The proposed system is designed to enhance accessibility for multilingual populations in Switzerland.
Nunc profana tractemus. Detecting Code-Switching in a Large Corpus of 16th Century Letters (2022.lrec-1)

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Challenge: a corpus of 16th century letters from and to the Zurich reformer Heinrich Bullinger has been preserved . a recent study investigated code-switching in these 8600 letters .
Approach: They investigate the automatic detection of code-switching in a 16th century letter exchange . they use a popular language identifier to bootstrap a word-based language classifier .
Outcome: The proposed language classifier bootstraps with a popular identifier on a small training corpus of 150 sentences per language.
DETECT: Determining Ease and Textual Clarity of German Text Simplifications (2026.eacl-long)

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Challenge: Current evaluation of German automatic text simplification relies on general-purpose metrics such as SARI, BLEU, and BERTScore.
Approach: They propose a German-specific metric that holistically evaluates ATS quality across all three dimensions of simplicity, meaning preservation, and fluency.
Outcome: The proposed metric achieves higher correlations with human judgments than widely used ATS metrics.
Audio Description Generation in the Era of LLMs and VLMs: A Review of Transferable Generative AI Technologies (2025.findings-naacl)

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Challenge: Audio descriptions (ADs) are acoustic commentaries designed to assist blind and visually impaired individuals in accessing digital media content.
Approach: They examine how state-of-the-art NLP and CV technologies can be applied to generate ADs . they identify essential research directions for the future .
Outcome: The proposed technologies can be applied to generate audio descriptions (ADs) the process is time-consuming and costly, and requires significant human effort . the authors identify key research directions for the future .

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