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Der Beitrag beschäftigt sich mit der Frage, wie und inwieweit korpusbasierte Ansätze zur Untersuchung und Bewertung von Sprachwandel beitragen können. Die Bewertung von Sprachwandel erscheint in dieser Hinsicht interessant, da sie erstens von größerem öffentlichen Interesse ist, zweitens nicht zu den Kernthemen der Sprachwissenschaft zählt und drittens sowohl die geisteswissenschaftlichen Aspekte der Sprachwissenschaft berührt als auch die empirischen, die eher für die so genannten harten Wissenschaften typisch sind. Letzteres trifft bei der Frage nach Sprachverfall (gutem vs. schlechtem Deutsch diachron) vermutlich unbestrittener zu als bei der Frage nach richtigem vs. falschem Deutsch, da zu ihrer Beantwortung offensichtlich einerseits empirische, messbare Kriterien herangezogen werden müssen, andererseits aber auch weitere Kriterien notwendig sind und es außerdem einer Entscheidung zur Einordnung und Gewichtung der verschiedenartigen Kriterien sowie einer Begründung dieser Entscheidung bedarf. Zur Annäherung an die Fragestellung werden zunächst gängige, leicht operationalisierbare Hypothesen zu Symptomen eines potenziellen Verfalls des Deutschen auf verschiedenen DeReKo-basierten Korpora überprüft und im Hinblick auf ihre Verallgemeinerbarkeit und Tragweite diskutiert. Im zweiten Teil werden weitere empirische Ansätze zur Untersuchung von Wandel, Variation und Dynamik skizziert, die zur Diskussion spezieller Aspekte von Sprachverfall beitragen könnten. Im Schlussteil werden die vorgestellten Ansätze in den Gesamtkontext einer sprachwissenschaftlichen Untersuchung von Sprachverfall gestellt und vor dem Hintergrund seines gesellschaftlichen Diskurses reflektiert.
Das Beispiel ist seit der Antike ein zentraler Gegenstand der abendländischen Diskussion. In dieser ersten umfassenden Monographie zur Linguistik des Beispiels wird deshalb eine interdisziplinäre Perspektive entfaltet, in der Ansätze aus Rhetorik, Philosophie, Pädagogik und Psychologie sowie linguistischen Ansätze zur Beispielforschung behandelt werden. Die sprachwissenschaftliche Beschäftigung mit Beispielen blieb bisher jedoch ein Randphänomen, obwohl Praktiken der Beispielverwendung in der Alltagskommunikation allgegenwärtig sind.
Orientiert an ›grounded theory‹, linguistischer Hermeneutik und Handlungssemantik wird hier ein Beispielbegriff erarbeitet, demzufolge das Beispielverwenden eine komplexe Form sprachlichen Handelns und eine fundamentale menschliche Denkbewegung darstellt, die darin besteht, einen Konnex zwischen Besonderem und Allgemeinem zu konstituieren. Hierauf basierend werden Beispiele anhand eines umfangreichen Korpus von Gesprächsdaten analysiert und kommunikative Muster, sprachliche Realisierungsformen sowie Funktionen des Beispielverwendens in der Interaktion herausgearbeitet.
Vernetzung statt Vereinheitlichung. Digitale Forschungsinfrastrukturen in den Geisteswissenschaften
(2014)
Die Entwicklung der digitalen Infrastruktur am Hamburger Zentrum für Sprachkorpora (HZSK) kann als Beispiel für die Evolution individueller technischer Einzellösungen hin zu fachspezifischen virtuellen Arbeits- und Forschungsumgebungen, die im Rahmen supranationaler Forschungsinfrastrukturen für die digitalen Geisteswissenschaften miteinander vernetzt sind, angesehen werden. Im Fokus steht im konkreten Fall des HZSK die Sicherung der langfristigen Zugänglichkeit von Forschungsdaten (multimedialen Daten gesprochener Sprache) durch die Entwicklung einer virtuellen Forschungsumgebung, die einerseits an die zentrenbasierte Forschungsinfrastruktur CLARIN-D angebunden ist und andererseits fachspezifische Benutzerschnittstellen schafft.
"FOLK is the ""Forschungs- und Lehrkorpus Gesprochenes Deutsch (FOLK)"" (eng.: research and teaching corpus of spoken German). The project has set itself the aim of building a corpus of German conversations which a) covers a broad range of interaction types in private, institutional and public settings, b) is sufficiently large and diverse and of sufficient quality to support different qualitative and quantitative research approaches, c) is transcribed, annotated and made accessible according to current technological standards, and d) is available to the scientific community on a sound legal basis and without unnecessary restrictions of usage. This paper gives an overview of the corpus design, the strategies for acquisition of a diverse range of interaction data, and the corpus construction workflow from recording via transcription an annotation to dissemination."
This paper presents the first release of the KiezDeutsch Korpus (KiDKo), a new language resource with multiparty spoken dialogues of Kiezdeutsch, a newly emerging language variety spoken by adolescents from multi-ethnic urban areas in Germany. The first release of the corpus includes the transcriptions of the data as well as a normalisation layer and part-of-speech annotations. In the paper, we describe the main features of the new resource and then focus on automatic POS tagging of informal spoken language. Our tagger achieves an accuracy of nearly 97% on KiDKo. While we did not succeed in further improving the tagger using ensemble tagging, we present our approach to using the tagger ensembles for identifying error patterns in the automatically tagged data.
As a result of legal restrictions the Google Ngram Corpora datasets are a) not accompanied by any metadata regarding the texts the corpora consist of and the data are b) truncated to prevent an indirect conclusion from the n-gram to the author of the text. Some of the consequences of this strategy are discussed in this article.
The Database for Spoken German (Datenbank für Gesprochenes Deutsch, DGD2, http://dgd.ids-mannheim.de) is the central platform for publishing and disseminating spoken language corpora from the Archive of Spoken German (Archiv für Gesprochenes Deutsch, AGD, http://agd.ids-mannheim.de) at the Institute for the German Language in Mannheim. The corpora contained in the DGD2 come from a variety of sources, some of them in-house projects, some of them external projects. Most of the corpora were originally intended either for research into the (dialectal) variation of German or for studies in conversation analysis and related fields. The AGD has taken over the task of permanently archiving these resources and making them available for reuse to the research community. To date, the DGD2 offers access to 19 different corpora, totalling around 9000 speech events, 2500 hours of audio recordings or 8 million transcribed words. This paper gives an overview of the data made available via the DGD2, of the technical basis for its implementation, and of the most important functionalities it offers. The paper concludes with information about the users of the database and future plans for its development.
Part-of-speech tagging (POS-tagging) of spoken data requires different means of annotation than POS-tagging of written and edited texts. In order to capture the features of German spoken language, a distinct tagset is needed to respond to the kinds of elements which only occur in speech. In order to create such a coherent tagset the most prominent phenomena of spoken language need to be analyzed, especially with respect to how they differ from written language. First evaluations have shown that the most prominent cause (over 50%) of errors in the existing automatized POS-tagging of transcripts of spoken German with the Stuttgart Tübingen Tagset (STTS) and the treetagger was the inaccurate interpretation of speech particles. One reason for this is that this class of words is virtually absent from the current STTS. This paper proposes a recategorization of the STTS in the field of speech particles based on distributional factors rather than semantics. The ultimate aim is to create a comprehensive reference corpus of spoken German data for the global research community. It is imperative that all phenomena are reliably recorded in future part-of-speech tag labels.
This paper gives an overview of recent developments in the German Reference Corpus DeReKo in terms of growth, maximising relevant corpus strata, metadata, legal issues, and its current and future research interface. Due to the recent acquisition of new licenses, DeReKo has grown by a factor of four in the first half of 2014, mostly in the area of newspaper text, and presently contains over 24 billion word tokens. Other strata, like fictional texts, web corpora, in particular CMC texts, and spoken but conceptually written texts have also increased significantly. We report on the newly acquired corpora that led to the major increase, on the principles and strategies behind our corpus acquisition activities, and on our solutions for the emerging legal, organisational, and technical challenges.
The annotation of parts of speech (POS) in linguistically annotated corpora is a fundamental annotation layer which provides the basis for further syntactic analyses, and many NLP tools rely on POS information as input. However, most POS annotation schemes have been developed with written (newspaper) text in mind and thus do not carry over well to text from other domains and genres. Recent discussions have concentrated on the shortcomings of present POS annotation schemes with regard to their applicability to data from domains other than newspaper text.
Recent work on error detection has shown that the quality of manually annotated corpora can be substantially improved by applying consistency checks to the data and automatically identifying incorrectly labelled instances. These methods, however, can not be used for automatically annotated corpora where errors are systematic and cannot easily be identified by looking at the variance in the data. This paper targets the detection of POS errors in automatically annotated corpora, so-called silver standards, showing that by combining different measures sensitive to annotation quality we can identify a large part of the errors and obtain a substantial increase in accuracy.
Newspapers became extremely popular in Germany during the 18th and 19th century, and thus increasingly influential for modern German. However, due to the lack of digitized historical newspaper corpora for German, this influence could not be analyzed systematically. In this paper, we introduce the Mannheim Corpus of Digital Newspapers and Magazines, which in its current release comprises 21 newspapers and magazines from the 18th and 19th century. With over 4.1 Mio tokens in about 650 volumes it currently constitutes the largest historical corpus dedicated to newspapers in German. We briefly discuss the prospect of the corpus for analyzing the evolution of news as a genre in its own right and the influence of contextual parameters such as region and register on the language of news. We then focus on one historically influential aspect of newspapers – their role in disseminating foreign words in German. Our preliminary quantitative results indeed indicate that newspapers use foreign words significantly more frequently than other genres, in particular belles lettres.
We describe a systematic and application-oriented approach to training and evaluating named entity recognition and classification (NERC) systems, the purpose of which is to identify an optimal system and to train an optimal model for named entity tagging DeReKo, a very large general-purpose corpus of contemporary German (Kupietz et al., 2010). DeReKo 's strong dispersion wrt. genre, register and time forces us to base our decision for a specific NERC system on an evaluation performed on a representative sample of DeReKo instead of performance figures that have been reported for the individual NERC systems when evaluated on more uniform and less diverse data. We create and manually annotate such a representative sample as evaluation data for three different NERC systems, for each of which various models are learnt on multiple training data. The proposed sampling method can be viewed as a generally applicable method for sampling evaluation data from an unbalanced target corpus for any sort of natural language processing.
This paper analyses paramedic emergency interaction as multimodal multiactivity. Based on a corpus of video-recordings of emergency drills performed by professional paramedics during advanced training, the focus is on paramedics’ participation in multiple joint projects which become simultaneously relevant. Simultaneity and fast succession of multiactivity does not only characterise work on the team level, but also the work profile of the individual paramedic. Participants have to coordinate their own participation in more than one joint project intrapersonally. In the data studied, three patterns of allocating multimodal resources stood out as routine ways of coordinating participation in two simultaneous projects intrapersonally:
1. Talk and hearing vs. manual action monitored by gaze,
2. Talk and hearing vs. gazing (and pointing),
3. Manual action vs. gaze (and talk and hearing).
Machine learning methods offer a great potential to automatically investigate large amounts of data in the humanities. Our contribution to the workshop reports about ongoing work in the BMBF project KobRA (http://www.kobra.tu-dortmund.de) where we apply machine learning methods to the analysis of big corpora in language-focused research of computer-mediated communication (CMC). At the workshop, we will discuss first results from training a Support Vector Machine (SVM) for the classification of selected linguistic features in talk pages of the German Wikipedia corpus in DeReKo provided by the IDS Mannheim. We will investigate different representations of the data to integrate complex syntactic and semantic information for the SVM. The results shall foster both corpus-based research of CMC and the annotation of linguistic features in CMC corpora.