Challenge: EPIC UdS is a multilingual corpus of simultaneous interpreting for English, German and Spanish.
Approach: They describe the creation and annotation of EPIC UdS, a multilingual corpus of simultaneous interpreting for English, German and Spanish.
Outcome: The proposed corpus includes transcripts suitable for research on more than one language pair and on interpreting with regard to German.

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The DReaM Corpus: A Multilingual Annotated Corpus of Grammars for the World’s Languages (2020.lrec-1)

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Challenge: Until recently, language descriptions were available in paper form only, with indexes as the only search aid.
Approach: They propose to digitize a multilingual corpus of language descriptions and annotate it with various meta, word, and text attributes to make searching and analysis easier and more useful.
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The WAW Corpus: The First Corpus of Interpreted Speeches and their Translations for English and Arabic (L18-1)

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Challenge: Using the corpus, we study the characteristics of interpreters' work and train machine translation systems.
Approach: They propose to build an interpreting corpus for Arabic and an Arabic corpus to study interpreters' work.
Outcome: The proposed corpus can be used for teaching interpreters and to train machine translation systems.
Simultaneous Translation (2020.emnlp-tutorials)

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Challenge: Simultaneous translation is a problem that has long been considered one of the hardest problems in AI . this tutorial will provide a deep understanding of the history and the recent advances in simultaneous translation.
Approach: This tutorial will examine the design and evaluation of policies for simultaneous translation . it will provide an overview of the history and recent advances in simultaneous translation.
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Simultaneous Interpretation Corpus Construction by Large Language Models in Distant Language Pair (2024.emnlp-main)

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Challenge: Existing siMT corpora are limited due to high costs and limited annotator capabilities.
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AMR Beyond the Sentence: the Multi-sentence AMR corpus (C18-1)

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Challenge: Abstract Meaning Representation (AMR) is limited to capturing the semantics of individual sentences.
Approach: They propose a corpus that annotates coreference and similar phenomena on top of existing AMRs.
Outcome: The proposed corpus is compared with existing corpora on sentence-level semantics . it shows that it can be used for information extraction and question answering .
The EDGeS Diachronic Bible Corpus (2020.lrec-1)

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Challenge: EDGeS is a diachronic and parallel corpus of Bible translations in Dutch, English, German and Swedish . it is intended to be used for longitudinal studies of complex verb constructions in Germanic .
Approach: They present the EDGeS Diachronic Bible Corpus, a diachronic corpus of Bible translations in Dutch, English, German and Swedish . they use a synchronically and synchronly parallel corpus to study complex verb constructions in Germanic .
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LibriS2S: A German-English Speech-to-Speech Translation Corpus (2022.lrec-1)

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Challenge: Recent advances in speech-to-text translation have led to significant improvements, but the availability of appropriate training data is limiting.
Approach: They propose a new text-to-speech and speech-tospech translation model that directly learns to generate the speech signal based on the pronunciation of the source language.
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Annotation and Automatic Classification of Aspectual Categories (P19-1)

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Challenge: Annotated resource for aspectual classification of German verb tokens in context.
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Universal Dependencies: Extensions for Modern and Historical German (2024.lrec-main)

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Challenge: a new UD treebank is being developed for Middle High German annotations . the annotation scheme is inconsistent with other treebanks for this period .
Approach: They propose to extend the UD scheme for modern and historical German by a range of tokens . they propose to use a treebank that is the first UD treebank for Middle High German .
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A Morphologically Annotated Corpus of Emirati Arabic (L18-1)

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Challenge: Emirati Arabic corpus is first large-scale morphologically manually annotated corpus . resources for dialectal Arabic NLP tasks are still lacking compared to those for modern standard Arabic (MSA).
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