EPIC-EuroParl-UdS: Information-Theoretic Perspectives on Translation and Interpreting

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Auteurs principaux: Kunilovskaya, Maria, Pollkläsener, Christina
Format: Preprint
Publié: 2026
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author Kunilovskaya, Maria
Pollkläsener, Christina
author_facet Kunilovskaya, Maria
Pollkläsener, Christina
contents This paper introduces an updated and combined version of the bidirectional English-German EPIC-UdS (spoken) and EuroParl-UdS (written) corpora containing original European Parliament speeches as well as their translations and interpretations. The new version corrects metadata and text errors identified through previous use, refines the content, updates linguistic annotations, and adds new layers, including word alignment and word-level surprisal indices. The combined resource is designed to support research using information-theoretic approaches to language variation, particularly studies comparing written and spoken modes, and examining disfluencies in speech, as well as traditional translationese studies, including parallel (source vs. target) and comparable (original vs. translated) analyses. The paper outlines the updates introduced in this release, summarises previous results based on the corpus, and presents a new illustrative study. The study validates the integrity of the rebuilt spoken data and evaluates probabilistic measures derived from base and fine-tuned GPT-2 and machine translation models on the task of filler particles prediction in interpreting.
format Preprint
id arxiv_https___arxiv_org_abs_2603_09785
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle EPIC-EuroParl-UdS: Information-Theoretic Perspectives on Translation and Interpreting
Kunilovskaya, Maria
Pollkläsener, Christina
Computation and Language
I.2.7; G.3; H.3.1; J.5
This paper introduces an updated and combined version of the bidirectional English-German EPIC-UdS (spoken) and EuroParl-UdS (written) corpora containing original European Parliament speeches as well as their translations and interpretations. The new version corrects metadata and text errors identified through previous use, refines the content, updates linguistic annotations, and adds new layers, including word alignment and word-level surprisal indices. The combined resource is designed to support research using information-theoretic approaches to language variation, particularly studies comparing written and spoken modes, and examining disfluencies in speech, as well as traditional translationese studies, including parallel (source vs. target) and comparable (original vs. translated) analyses. The paper outlines the updates introduced in this release, summarises previous results based on the corpus, and presents a new illustrative study. The study validates the integrity of the rebuilt spoken data and evaluates probabilistic measures derived from base and fine-tuned GPT-2 and machine translation models on the task of filler particles prediction in interpreting.
title EPIC-EuroParl-UdS: Information-Theoretic Perspectives on Translation and Interpreting
topic Computation and Language
I.2.7; G.3; H.3.1; J.5
url https://arxiv.org/abs/2603.09785