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In German oral discourse, previous research has shown that okay can be used both as a response token (e.g., for agreeing with the previous turn or for claiming a certain degree of understanding) and as a discourse marker (e.g., for closing conversational topics or sequences and/or indicating transitions). This contribution focuses on the use of okay as a response token and how it is connected with the speakers’ interactional state of knowledge (their understanding, their assumptions etc.). The analysis is based on video recorded everyday conversations in German and a sequential, micro-analytic approach (multimodal conversation analysis). The main function of conversational okay in the selected data set is related to indicating the acceptance of prior information. By okay, speakers however claim acceptance of a piece of information that they can’t verify or check. The analysis contrasts different sequences containing okay only with sequences in which change-of-state tokens such as ah and achso co-occur with okay. This illustrates that okay itself does not index prior information as new, and that it is not used for agreeing with or for confirming prior information. Instead it enables the speaker to adopt a kind of neutral, “non-agreeing” position towards a given piece of information.
The newest generation of speech technology caused a huge increase of audio-visual data nowadays being enhanced with orthographic transcripts such as in automatic subtitling in online platforms. Research data centers and archives contain a range of new and historical data, which are currently only partially transcribed and therefore only partially accessible for systematic querying. Automatic Speech Recognition (ASR) is one option of making that data accessible. This paper tests the usability of a state-of-the-art ASR-System on a historical (from the 1960s), but regionally balanced corpus of spoken German, and a relatively new corpus (from 2012) recorded in a narrow area. We observed a regional bias of the ASR-System with higher recognition scores for the north of Germany vs. lower scores for the south. A detailed analysis of the narrow region data revealed – despite relatively high ASR-confidence – some specific word errors due to a lack of regional adaptation. These findings need to be considered in decisions on further data processing and the curation of corpora, e.g. correcting transcripts or transcribing from scratch. Such geography-dependent analyses can also have the potential for ASR-development to make targeted data selection for training/adaptation and to increase the sensitivity towards varieties of pluricentric languages.
Der Beitrag stellt die wissenschaftlichen und methodologischen Herausforderungen für die Erstellung einer innovativen, korpusbasierten lexikografischen Ressource zur Lexik des gesprochenen Deutsch in der Interaktion vor und zeigt neue Wege für lexikografische Arbeiten auf. Neben allgemeinen Projektinformationen zu den Ausgangspunkten, der Datengrundlage, den Methoden, Zielen und dem konkreten Gegenstandsbereich werden ausgewählte Ergebnisse von zwei projektbezogenen empirischen Studien zu Erwartungshaltungen an eine lexikografische Ressource des gesprochenen Deutsch präsentiert. Für korpusbasierte quantitative Informationen werden die Möglichkeiten eines Tools, welches im Rahmen des Projekts entwickelt wurde, aufgezeigt. Außerdem wird ein Einblick in die konzeptionellen und methodologischen Überlegungen zur Mikrostruktur der geplanten Ressource gegeben.
Except for some recent advances in spoken language lexicography (cf. Verdonik & Sepesy Maučec 2017, Hansen & Hansen 2012, Siepmann 2015), traditional lexicographic work is mainly oriented towards the written language. In this paper, we describe a method we used to identify relevant headword candidates for a lexicographic resource for spoken language that is currently being developed at the Institute for the German Language (IDS, Mannheim). We describe the challenges of the headword selection for a dictionary of spoken language, and having made considerations regarding our headword concept, we present the corpus-based procedures that we used in order to facilitate the headword selection. After presenting the results regarding the selection of one-word lemmas, we discuss the opportunities and limitations of our approach.
This paper gives an insight into the basic concepts for a corpus-based lexical resource of spoken German, which is being developed by the project "The Lexicon of Spoken German"(Lexik des gesprochenen Deutsch, LeGeDe) at the "Institute for the German Language" (Institut für Deutsche Sprache, IDS) in Mannheim. The focus of the paper is on initial ideas of semi-automatic and automatic resources that assist the quantitative analysis of the corpus data for the creation of dictionary content. The work is based on the "Research and Teaching Corpus of Spoken German" (Forschungs- und Lehrkorpus Gesprochenes Deutsch, FOLK).