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This paper presents the prototype of a lexicographic resource for spoken German in interaction, which was conceived within the framework of the LeGeDe-project (LeGeDe=Lexik des gesprochenen Deutsch). First of all, it summarizes the theoretical and methodological approaches that were used for the initial planning of the resource. The headword candidates were selected by analyzing corpus-based data. Therefore, the data of two corpora (written and spoken German) were compared with quantitative methods. The information that was gathered on the selected headword candidates can be assigned to two different sections: meanings and functions in interaction.
Additionally, two studies on the expectations of future users towards the resource were carried out. The results of these two studies were also taken into account in the development of the prototype. Focusing on the presentation of the resource’s content, the paper shows both the different lexicographical information in selected dictionary entries, and the information offered by the provided hyperlinks and external texts. As a conclusion, it summarizes the most important innovative aspects that were specifically developed for the implementation of such a resource.
Classical null hypothesis significance tests are not appropriate in corpus linguistics, because the randomness assumption underlying these testing procedures is not fulfilled. Nevertheless, there are numerous scenarios where it would be beneficial to have some kind of test in order to judge the relevance of a result (e.g. a difference between two corpora) by answering the question whether the attribute of interest is pronounced enough to warrant the conclusion that it is substantial and not due to chance. In this paper, I outline such a test.
Der vorliegende Beitrag setzt sich mit dem computergestützten Transkriptionsverfahren arabisch-deutscher Gesprächsdaten für interaktionsbezogene Untersuchungen auseinander. Zunächst werden wesentliche methodische Herausforderungen der gesprächsanalytischen Arbeit adressiert: Hinsichtlich der derzeitigen Korpustechnologie ermöglicht die Verwendung von arabischen Schriftzeichen in einem mehrsprachigen, bidirektionalen Transkript keine analysegerechte Rekonstruktion von Reziprozität, Linearität und Simultaneität sprachlichen Handelns. Zudem ist die Verschriftung von arabischen Gesprächsdaten aufgrund der unzureichenden (gesprächsanalytischen) Beschäftigung mit den standardfernen Varietäten und gesprochensprachlichen Phänomenen erschwert. Daher widmet sich der zweite Teil des Beitrags den bisher erarbeiteten und erprobten Lösungsansätzen ̶ einem stringenten, gesprächsanalytisch fundierten Transkriptionssystem für gesprochenes Arabisch.
Common Crawl is a considerably large, heterogeneous multilingual corpus comprised of crawled documents from the internet, surpassing 20TB of data and distributed as a set of more than 50 thousand plain text files where each contains many documents written in a wide variety of languages. Even though each document has a metadata block associated to it, this data lacks any information about the language in which each document is written, making it extremely difficult to use Common Crawl for monolingual applications. We propose a general, highly parallel, multithreaded pipeline to clean and classify Common Crawl by language; we specifically design it so that it runs efficiently on medium to low resource infrastructures where I/O speeds are the main constraint. We develop the pipeline so that it can be easily reapplied to any kind of heterogeneous corpus and so that it can be parameterised to a wide range of infrastructures. We also distribute a 6.3TB version of Common Crawl, filtered, classified by language, shuffled at line level in order to avoid copyright issues, and ready to be used for NLP applications.
Since 2013 representatives of several French and German CMC corpus projects have developed three customizations of the TEI-P5 standard for text encoding in order to adapt the encoding schema and models provided by the TEI to the structural peculiarities of CMC discourse. Based on the three schema versions, a 4th version has been created which takes into account the experiences from encoding our corpora and which is specifically designed for the submission of a feature request to the TEI council. On our poster we would present the structure of this schema and its relations (commonalities and differences) to the previous schemas.
The paper deals with the process of computer-aided transcription regarding Arabic-German data material for interaction-based studies. First of all, it sheds light upon some major methodological challenges posed by the conversation-analytic approaches: due to current corpus technology, the reciprocity, linearity, and simultaneity of linguistic activities cannot be reconstructed in an analytically proper way when using the Arabic characters in multilingual and bidirectional transcripts. The difficulty of transcribing Arabic encounters is also compounded by the fact that Spoken Arabic as well as its varieties and phenomena have not been standardised enough (for conversation-analytic purposes). Therefore, the second part of this paper is dedicated to preliminary, self-developed solutions, namely a systematic method for transcribing Spoken Arabic.
Das Archiv für Gesprochenes Deutsch (AGD, Stift/Schmidt 2014) am Leibniz-Institut für Deutsche Sprache ist ein Forschungsdatenzentrum für Korpora des gesprochenen Deutsch. Gegründet als Deutsches Spracharchiv (DSAv) im Jahre 1932 hat es über Eigenprojekte, Kooperationen und Übernahmen von Daten aus abgeschlossenen Forschungsprojekten einen Bestand von bald 100 Variations-, Interview- und Gesprächskorpora aufgebaut, die u. a. dialektalen Sprachgebrauch, mündliche Kommunikationsformen oder die Sprachverwendung bestimmter Sprechertypen oder zu bestimmten Themen dokumentieren. Heute ist dieser Bestand fast vollständig digitalisiert und wird zu einem großen Teil der wissenschaftlichen Gemeinschaft über die Datenbank für Gesprochenes Deutsch (DGD) im Internet zur Nutzung in Forschung und Lehre angeboten.