P2: Mündliche Korpora
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This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are the depositors’ questionnaire and automatic quality assurance, both developed as web applications. They are accompanied by a Knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we split linguistic data into three resource classes (data deposits, collections and corpora). The class of a resource defines the strictness of the quality assurance it should undergo. This division is introduced so that too strict quality criteria do not prevent researchers from depositing their data.
This paper presents the QUEST project and describes concepts and tools that are being developed within its framework. The goal of the project is to establish quality criteria and curation criteria for annotated audiovisual language data. Building on existing resources developed by the participating institutions earlier, QUEST also develops tools that could be used to facilitate and verify adherence to these criteria. An important focus of the project is making these tools accessible for researchers without substantial technical background and helping them produce high-quality data. The main tools we intend to provide are a questionnaire and automatic quality assurance for depositors of language resources, both developed as web applications. They are accompanied by a knowledge base, which will contain recommendations and descriptions of best practices established in the course of the project. Conceptually, we consider three main data maturity levels in order to decide on a suitable level of strictness of the quality assurance. This division has been introduced to avoid that a set of ideal quality criteria prevent researchers from depositing or even assessing their (legacy) data. The tools described in the paper are work in progress and are expected to be released by the end of the QUEST project in 2022.
We present a collection of (currently) about 5.500 commands directed to voice-controlled virtual assistants (VAs) by sixteen initial users of a VA system in their homes. The collection comprises recordings captured by the VA itself and with a conditional voice recorder (CVR) selectively capturing recordings including the VA-directed commands plus some surrounding context. Next to a description of the collection, we present initial findings on the patterns of use of the VA systems during the first weeks after installation, including usage timing, the development of usage frequency, distributions of sentence structures across commands, and (the development of) command success rates. We discuss the advantages and disadvantages of the applied collection-specific recording approach and describe potential research questions that can be investigated in the future, based on the collection, as well as the merit of combining quantitative corpus linguistic approaches with qualitative in-depth analyses of single cases.
In this paper, we present an overview of freely available web applications providing online access to spoken language corpora. We explore and discuss various solutions with which the corpus providers and corpus platform developers address the needs of researchers who are working with spoken language. The paper aims to contribute to the long-overdue exchange and discussion of methods and best practices in the design of online access to spoken language corpora.
Die Dokumentation und Untersuchung deutscher Sprachinselvarietäten war schon immer eine der wichtigsten Aufgaben der germanistischen Sprachwissenschaft. Mittlerweile stellt sich aber immer öfter die Frage der Nachhaltigkeit der erhobenen Spachinseldaten. Insbesondere in Bezug auf die vom Sprachtod bedrohten Varietäten, wie z.B. im Fall der russlanddeutschen Dialekte aus den noch intakten Sprachinseln der ehemaligen Sowjetunion, ist es äußerst wichtig, die existierenden Audioaufnahmen systematisch und dauerhaft zu archivieren. Aber nicht nur die Archivierung, sondern auch der freie und unkomplizierte Zugang zu diesen Materialien ist ein wesentlicher Aspekt im Konzept der Nachhaltigkeit. Wie sollte dieser Zugang aber gestaltet sein und in welcher Form sollen die Daten präsentiert werden? Auf genau diese Frage ist das Projekt „Elektronisches Wörterbuch. Ein Online-Informationsangebot zu Sprache und Dialekten der Russlanddeutschen" eingegangen. In diesem Projekt wurden historische Tonaufnahmen russlanddeutscher Dialekte linguistisch aufbereitet und in Form einer strukturierten Russlanddeutschen Dialektdatenbank (RuDiDat) online veröffentlicht. Diese Datenbank ist frei verfügbar und ermöglicht die Recherche im Korpus des Russlanddeutschen. Der vorliegende Beitrag stellt die Datenbank vor und thematisiert Herausforderungen, die durch unterschiedliche Ausprägungsformen des Russlanddeutschen entstehen könnten, wenn man die im Internet freigegebenen Sprachinseldaten für vergleichende Analysen heranzieht.
KonsortSWD ist das NFDI Konsortium für die Sozial-, Verhaltens-, Bildungs- und Wirtschaftswissenschaften. Für die äußerst vielfältigen Datentypen und Forschungsmethoden bauen die Beteiligten im Rahmen der NFDI eine bereits bestehende Forschungsdateninfrastruktur aus und ergänzen neue integrierende Dienste. Basis sind die heute 41 vom Rat für Sozial- und Wirtschaftsdaten akkreditierten Forschungsdatenzentren (FDZ). FDZ sind Spezialsammlungen zu jeweils spezifischen Forschungsdaten, z.B. aus der qualitativen Sozialforschung, und können so Forschende auf Basis einer ausführlichen Expertise zu diesen Daten beraten. Neben der Unterstützung der FDZ baut KonsortSWD auch neue Dienste in den Bereichen Datenproduktion, Datenzugang und Technische Lösungen auf.
While the role of intentions in the constitution of actions gives rise to complex and heavily controversial questions, it appears to be indisputable that action ascription in interaction mostly does without any overt ascription of intention. Yet, sometimes participants explicitly ascribe intentions to their interlocutors in order to make sense of their prior actions. The chapter examines intention ascriptions in response to a partner’s adjacent prior turn using the German modal verb construction willst du/wollen Sie (do you want). The analysis focuses on the aspect of the prior action the intention ascription addresses (action type, projected next action, motive etc.), the action the intention ascription performs itself, and the next action they make relevant from the prior speaker. It was found that intention ascriptions are used to clarify and intersubjectively ground the meaning of the prior turn, which seems otherwise underspecified, ambiguous or puzzling. Yet, they are also used to adumbrate criticism, e.g., that the prior turn projects a course of future actions which is considered to be inadequate, or to expose a concealed, problematic allegedly “real” meaning of the prior turn.