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Das Ziel des Beitrags ist es, die Merkmale von Kommunikationsstörungen in Sport-Interviews aus Sicht der Interviewten festzustellen und zu analysieren. Die empirische Forschungsbasis besteht aus ukrainisch- und deutschsprachigen Videointerviews aus den Jahren 2010 bis 2019, die entweder im Fernsehen gesendet oder für YouTube produziert wurden. Die Ergebnisse der Studie ermöglichten es, die charakteristischen Merkmale von Abweichungen als Kommunikationsstörungen in Sport-Interviews auf drei Ebenen der kommunikativen Gattung zu identifizieren: auf der außenstrukturellen, binnenstrukturellen und situativen Ebene. Sowohl gemeinsame Merkmale von Kommunikationsstörungen als auch Unterschiede in den ukrainisch- und deutschsprachigen Sport-Interviews wurden bestimmt. Die Ergebnisse der Studie zeigen, dass die Arten von Kommunikationsstörungen in Sport-Interviews im Ukrainischen und Deutschen universell sind, sie spiegeln jedoch die nationalen und kulturellen Besonderheiten angesichts der Merkmale beider Sprachen und jeder Sprachkultur wider.
We describe a simple procedure for the automatic creation of word-level alignments between printed documents and their respective full-text versions. The procedure is unsupervised, uses standard, off-the-shelf components only, and reaches an F-score of 85.01 in the basic setup and up to 86.63 when using pre- and post-processing. Potential areas of application are manual database curation (incl. document triage) and biomedical expression OCR.
In conversation, speakers need to plan and comprehend language in parallel in order to meet the tight timing constraints of turn taking. Given that language comprehension and speech production planning both require cognitive resources and engage overlapping neural circuits, these two tasks may interfere with one another in dialogue situations. Interference effects have been reported on a number of linguistic processing levels, including lexicosemantics. This paper reports a study on semantic processing efficiency during language comprehension in overlap with speech planning, where participants responded verbally to questions containing semantic illusions. Participants rejected a smaller proportion of the illusions when planning their response in overlap with the illusory word than when planning their response after the end of the question. The obtained results indicate that speech planning interferes with language comprehension in dialogue situations, leading to reduced semantic processing of the incoming turn. Potential explanatory processing accounts are discussed.
Ungoliant: An optimized pipeline for the generation of a very large-scale multilingual web corpus
(2021)
Since the introduction of large language models in Natural Language Processing, large raw corpora have played a crucial role in Computational Linguistics. However, most of these large raw corpora are either available only for English or not available to the general public due to copyright issues. Nevertheless, there are some examples of freely available multilingual corpora for training Deep Learning NLP models, such as the OSCAR and Paracrawl corpora. However, they have quality issues, especially for low-resource languages. Moreover, recreating or updating these corpora is very complex. In this work, we try to reproduce and improve the goclassy pipeline used to create the OSCAR corpus. We propose a new pipeline that is faster, modular, parameterizable, and well documented. We use it to create a corpus similar to OSCAR but larger and based on recent data. Also, unlike OSCAR, the metadata information is at the document level. We release our pipeline under an open source license and publish the corpus under a research-only license.
Making research data publicly available for evaluation or reuse is a fundamental part of good scientific practice. However, regulations such as copyright law can prevent this practice and thereby hamper scientific progress. In Germany, text-based research disciplines have for a long time been mostly unable to publish corpora made from material outside of the public domain, effectively excluding contemporary works. While there are approaches to obfuscate text material in a way that it is no longer covered by the original copyright, many use cases still require the raw textual context for evaluation or follow-up research. Recent changes in copyright now permit text and data mining on copyrighted works. However, questions regarding reusability and sharing of such corpora at a later time are still not answered to a satisfying degree. We propose a workflow that allows interested third parties to access customized excerpts of protected corpora in accordance with current German copyright law and the soon to be implemented guidelines of the Digital Single Market directive. Our prototype is a very lightweight web interface that builds on commonly used repository software and web standards.
Content
1 Substituto - A Synchronous Educational Language Game for Simultaneous Teaching and Crowdsourcing
Marianne Grace Araneta, Gülsen Eryigit, Alexander König, Ji-Ung Lee, Ana Luís, Verena Lyding, Lionel Nicolas, Christos Rodosthenous and Federico Sangati
2 The Teacher-Student Chatroom Corpus
Andrew Caines, Helen Yannakoudakis, Helena Edmondson, Helen Allen, Pascual Pérez-Paredes, Bill Byrne and Paula Buttery
3 Polygloss - A conversational agent for language practice
Etiene da Cruz Dalcol and Massimo Poesio
4 Show, Don’t Tell: Visualising Finnish Word Formation in a Browser-Based Reading Assistant
Frankie Robertson
In this paper we investigate the problem of grammar inference from a different perspective. The common approach is to try to infer a grammar directly from example sentences, which either requires a large training set or suffers from bad accuracy. We instead view it as a problem of grammar restriction or sub-grammar extraction. We start from a large-scale resource grammar and a small number of examples, and find a sub-grammar that still covers all the examples. To do this we formulate the problem as a constraint satisfaction problem, and use an existing constraint solver to find the optimal grammar. We have made experiments with English, Finnish, German, Swedish and Spanish, which show that 10–20 examples are often sufficient to learn an interesting domain grammar. Possible applications include computer-assisted language learning, domain-specific dialogue systems, computer games, Q/A-systems, and others.
Preface
(2020)
We introduce a novel scientific document processing task for making previously inaccessible information in printed paper documents available to automatic processing. We describe our data set of scanned documents and data records from the biological database SABIO-RK, provide a definition of the task, and report findings from preliminary experiments. Rigorous evaluation proved challenging due to lack of gold-standard data and a difficult notion of correctness. Qualitative inspection of results, however, showed the feasibility and usefulness of the task.