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Heute wird mehr geschrieben als je zuvor und die digitale Kommunikation trägt wesentlich dazu bei; ein großer Teil des heutigen Schreibens ist dialogisches Schreiben im Alltag. Konsequenterweise wird die Online-Kommunikation zunehmend Thema in Bildungskontexten und in der Deutschdidaktik. Offen ist aber weiterhin, wie Texte des interaktionsorientierten Schreibens bewertet werden sollen, die sich von solchen des textorientierten Schreibens in vielerlei Hinsicht unterscheiden können. Während es für textorientiertes Schreiben Normen gibt, die in Sprachkodizes erfasst sind, ist es nicht klar, was der Bezugspunkt für interaktionsorientierte Texte sein könnte. In diesem Beitrag analysieren wir die Verwendung von Konnektoren in der Online-Kommunikation und die Repräsentation von online-spezifischen Besonderheiten in Sprachressourcen. Die Ergebnisse zeigen, dass spezifische Online-Verwendungsweisen von Konnektoren in Sprachkodizes kaum berücksichtigt und beschrieben werden.
Das Kommunizieren in Sozialen Medien und der Umgang mit Hypertexten ist im Jahr 2020 kein Randphänomen mehr. Die sprachlichen Besonderheiten internetbasierter Kommunikation und Sozialer Medien sind mittlerweile auch gut erforscht und beschrieben, allerdings werden diese bislang in deutschen Grammatiken, mit Ausnahme von Hoffmann (2014), allenfalls am Rande behandelt. Selbst neuere Ansätze zur Textanalyse, z. B. Ágel (2017), konzentrieren sich auf gestaltstabile, linear organisierte Schrifttexte. Dasselbe gilt für Ansätze, die primär für die Bewertung von Schreibprodukten in Bildungskontexten entwickelt wurden.
The annual microcensus provides Germany’s most important official statistics. Unlike a census it does not cover the whole population, but a representative 1%-sample of it. In 2017, the German microcensus asked a question on the language of the population, i.e. ‘Which language is mainly spoken in your household?’ Unfortunately, the question, its design and its position within the whole microcensus’ questionnaire feature several shortcomings. The main shortcoming is that multilingual repertoires cannot be captured by it. Recommendations for the improvement of the microcensus’ language question: first and foremost the question (i.e. its wording, design, and answer options) should make it possible to count multilingual repertoires.
Preface
(2020)
In diesem Beitrag stellen wir die Ergebnisse einer Studie über die Intonation von Frageaktivitäten in deutschen Alltagsgesprächen vor. Unsere Untersuchung erforscht, inwieweit die Intonation zur Kontextualisierung von konversationellen Fragen beiträgt. In der Analyse stützen wir uns auf das autosegmental-metrische Modell von Peters und das taxonomische Modell der interaktionalen Prosodieforschung von Selting. Diese Modelle beschreiben jeweils phonologische oder pragmatische Aspekte der Frageintonation, zwei Dimensionen, die für sich genommen, keine vollständige Beschreibung liefern können. Auf der Grundlage authentischer Gesprächsdaten aus dem Korpus FOLK argumentieren wir für die Kompatibilität des autosegmental-metrischen Modells von Peters und des taxonomischen Modells der Frageintonation von Selting. Die Merkmale aus beiden Modellen lassen sich zu Bündeln kombinieren, die es erlauben, die Intonation von Fragen zu erfassen.
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.
The CMDI Explorer
(2020)
We present the CMDI Explorer, a tool that empowers users to easily explore the contents of complex CMDI records and to process selected parts of them with little effort. The tool allows users, for instance, to analyse virtual collections represented by CMDI records, and to send collection items to other CLARIN services such as the Switchboard for subsequent processing. The CMDI Explorer hence adds functionality that many users felt was lacking from the CLARIN tool space.
This paper addresses long-term archival for large corpora. Three aspects specific to language resources are focused, namely (1) the removal of resources for legal reasons, (2) versioning of (unchanged) objects in constantly growing resources, especially where objects can be part of multiple releases but also part of different collections, and (3) the conversion of data to new formats for digital preservation. It is motivated why language resources may have to be changed, and why formats may need to be converted. As a solution, the use of an intermediate proxy object called a signpost is suggested. The approach will be exemplified with respect to the corpora of the Leibniz Institute for the German Language in Mannheim, namely the German Reference Corpus (DeReKo) and the Archive for Spoken German (AGD).
Signposts for CLARIN
(2020)
An implementation of CMDI-based signposts and its use is presented in this paper. Arnold et al. 2020 present Signposts as a solution to challenges in long-term preservation of corpora, especially corpora that are continuously extended and subject to modification, e.g., due to legal injunctions, but also may overlap with respect to constituents, and may be subject to migrations to new data formats. We describe the contribution Signposts can make to the CLARIN infrastructure and document the design for the CMDI profile.
When humans have a conversation with one-another, they generally take turns speaking one after the other without overlapping each others talk or leaving silence between turns for long stretches of time. Previous research has shown that conversation is a structured practice following rules that help interlocutors to manage the flow of conversation interactively. While at the beginning of a conversation it remains open who will speak when about what and for how long, interlocutors regulate the flow of conversation as it unfolds. One basic set of rules that interlocutors operate with governs the allocation of speaking turns, with the central rule stating that whoever starts speaking first at a point in time when speaker change becomes relevant has the rights and obligations to produce the next turn. The organization of turn allocation, therefore, is one reason for conversational turn taking to be so remarkably fast, with the beginnings of turns most often being quite accurately aligned with the ends of the previous turns. Observations of this outstanding speed of turn taking gave rise to a number of questions concerning language processing in conversational situations. The studies presented in this thesis investigate some of these questions from the perspective of the current listener preparing to be the next speaker who will respond to the current turn.
The study presented in Chapter 2 investigates when next speakers begin to plan their own turn with respect to two points in time, (i) the moment when the incoming turn’s message becomes clear enough to make response planning possible and (ii) the moment when the incoming turn terminates. Results of previous studies were inconclusive about the timing of language planning in conversation, with evidence in favour of both late and early response planning. Furthermore, previous studies presented both evidence as well as counter evidence indicating that response planning depends or does not depend on an accurate prediction of the timing of the incoming turn’s end. The study presented here makes use of a novel experimental paradigm which includes a dialogic task that participants need to fulfil in response to critical utterances by a confederate. These critical utterances were structured, on the one hand, so that their message became clear either only at the end of the turn or before the end of the turn, and, on the other hand, so that it was either predictable or not predictable when exactly the turn would end. Participant’s eye-movements as well as their response latencies indicated that they always planned their next turn as early as possible, irrespective of the predictability of the incoming turn’s end. The presented results provide evidence in favour of models of turn taking that predict speech planning to happen in overlap with the incoming turn.
Having established that next speakers begin to plan their turn in overlap, the study presented in Chapter 3 goes more into detail investigating to which depth language planning progresses while the incoming turn is still unfolding. To this end, a number of psycholinguistic paradigms were combined. In the study’s main experiment, participants had to fulfil a switch-task in which they switched from picture naming in response to an auditorily presented question to making a lexical decision. By manipulating the relatedness of the word for lexical decision with the picture that was prepared to be named before the task-switch it was possible to draw inferences on which processing stages were entered during the speech production process in overlap with the incoming turn. Participants’ behavioural responses in the lexical decision task revealed that they entered the stage of phonological encoding while the incoming turn was still unfolding, showing that planning in overlap is not limited to conceptual preparation but includes all sub-processes of formulation.
Given that speech production regularly enters the stages of formulation in overlap with the incoming turn, as shown in Chapters 2 and 3, the question arises whether planning the next turn in overlap is cognitively more demanding than during the gap between turns. This question is approached in the study presented in Chapter 4 by measuring pupillometric responses of participants in a dialogic task. An increase in pupil diameter during a cognitive task is indicative of increased processing load, and pupillometric responses to planning in overlap with the incoming turn were found to be greater than responses to planning in the gap between turns. These results show that planning in overlap is more demanding than planning during the gap, even though it is highly practiced by speakers.
After Chapters 2 to 4 investigated the timing and mechanisms of speech planning in conversation, Chapter 5 turns towards the timing of articulation of a planned turn, asking the question what sources of information next speakers use to time the articulation of a planned utterance to start closely after the incoming turn comes to an end. In this Chapter’s study, participants taking turns with a confederate responded to utterances containing or not containing different cues to the location of the incoming turn’s end. Participants made use of lexical and turn-final intonational cues, but not of turn-initial intonational cues, responding faster when the relevant cues were present than when they were not present. These results show that the timing of turn initiation in next speakers depends on the recognition of the incoming turn’s point of completion and not merely on the progress in planning the next turn.
All evidence presented in Chapters 2 to 5 is summed up and bundled together in a cognitive model of turn taking, which is being presented in Chapter 6. This model assumes, centrally, that the planning of a turn and the timing of its articulation are separate cognitive processes that run in parallel in any next speaker during conversation. Planning generally starts as early as possible, often in overlap with the incoming turn, while the timing of articulation depends on the next speaker’s level of certainty that speaker change has become relevant at a particular moment, with a number of cues to the end of the incoming turn leading to an increase of certainty. Next turns are assumed to often be planned down to fully formulated utterance plans including their phonological form as early as possible on the basis of anticipations of the incoming turn’s message, which are created with the help of the general and situational knowledge about the world, the current speaker and her intentions, as well as the input that has been received so far. The level of certainty that speaker change becomes relevant rises or decreases as lexico-syntactic, prosodic, and pragmatic projections about the development of the current turn are fulfilled or not fulfilled. As the incoming turn progresses towards its end as was projected by the current listener, he becomes certain that speaker change becomes relevant and will initiate articulation of the prepared next turn. Viewing these two processes, planning a next turn and timing of its articulation, as separate makes it possible to explain the observable fast timing of turn taking while still modelling the allocation of turns as interactionally managed by interlocutors — a considerable advantage of the presented model compared to more traditional perspectives on turn taking and conversation.
To ensure short gaps between turns in conversation, next speakers regularly start planning their utterance in overlap with the incoming turn. Three experiments investigate which stages of utterance planning are executed in overlap. E1 establishes effects of associative and phonological relatedness of pictures and words in a switch-task from picture naming to lexical decision. E2 focuses on effects of phonological relatedness and investigates potential shifts in the time-course of production planning during background speech. E3 required participants to verbally answer questions as a base task. In critical trials, however, participants switched to visual lexical decision just after they began planning their answer. The task-switch was time-locked to participants' gaze for response planning. Results show that word form encoding is done as early as possible and not postponed until the end of the incoming turn. Hence, planning a response during the incoming turn is executed at least until word form activation.
In this Paper, we describe a schema and models which have been developed for the representation of corpora of computer-mediated communicatin (CMC corpora) using the representation framework provided by the Text Encoding Initiative (TEI). We characterise CMC discourse as dialogic, sequentially organised interchange between humans and point out that many features of CMC are not adequately handled by current corpus encoding schemas and tools. We formulate desiderata for a representation of CMC in encoding schemes and argue why the TEI is a suitable framework for the encoding of CMC corpora. We propose a model of basic CMC units (utterances, posts, and nonverbal activities) and the macro- and micro-level structures of interactions in CMC environments. Based on these models, we introduce CMC-core, a TEI customisation for the encoding of CMC corpora, which defines CMC-specific encoding features on the four levels of elements, model classes, attribute classes, and modules of the TEI infrastructure. The description of our customisation is illustrated by encoding examples from corpora by researchers of the TEI SIG CMC, representing a variety of CMC genres, i.e. chat, wiki talk, twitter, blog, and Second Life interactions. The material described, i.e. schemata, encoding examples, and documentation, is available from the of the TEI CMC SIG Wiki and will accompany a feature request to the TEI council in late 2019.
Linguistic Variation and Change in 250 Years of English Scientific Writing: A Data-Driven Approach
(2020)
We trace the evolution of Scientific English through the Late Modern period to modern time on the basis of a comprehensive corpus composed of the Transactions and Proceedings of the Royal Society of London, the first and longest-running English scientific journal established in 1665. Specifically, we explore the linguistic imprints of specialization and diversification in the science domain which accumulate in the formation of “scientific language” and field-specific sublanguages/registers (chemistry, biology etc.). We pursue an exploratory, data-driven approach using state-of-the-art computational language models and combine them with selected information-theoretic measures (entropy, relative entropy) for comparing models along relevant dimensions of variation (time, register). Focusing on selected linguistic variables (lexis, grammar), we show how we deploy computational language models for capturing linguistic variation and change and discuss benefits and limitations.
Sogenannte „Pragmatikalisierte Mehrworteinheiten“ sind im Deutschen hochfrequent und unterliegen bisweilen tiefgreifenden phonetischen Reduktionsprozessen. Diese können Realisierungsvarianten hervorbringen, die in der Rückschau auf mehr als eine lexematische Ursprungsform zurückführbar sind. Die vorliegende Studie untersucht mit [ˈzɐmɐ] einen besonders prägnanten Fall dieser Art anhand eines Perzeptionsexperimentes.
This chapter focuses on the formation of adverbs from a corpuslinguistic perspective, providing an overview of adverb formation patterns in German that includes frequencies and hints to productivity as well as combining quantitative methods and theoretically founded hypotheses to address questions that concern possible grammaticalization paths in domains that are formally marked by prepositional elements or inflectional morphology (in particular, superlative or superlative-derived forms). Within our collection of adverb types from the project corpus, special attention is paid to adverbs built from primary prepositions. The data suggest that generally, such adverb formation involves the saturation of the internal argument slot of the relation-denoting preposition. In morphologically regular formations with the preposition in final position, pronominal forms like da ‘there’, hier ‘here’, wo ‘where’ as well as hin ‘hither’ and her ‘thither’ serve to derive adverbs. On the other hand, morphologically irregular formations with the preposition – in particular: zu ‘to’ or vor ‘before, in front of’ – in initial posi-tion show traits of syntactic origin such as (remnants of) inflectional morphology. The pertaining adverb type dominantly saturates the internal argument slot by means of universal quantification that is part and parcel as well of the derivation of superlatives and demonstrably fuels the productivity of the pertaining formation pattern.
Die vorgestellte Studie untersucht die Anteile unterschiedlicher Redewiedergabeformen im Vergleich zwischen zwei Literaturtypen von gegensätzlichen Enden des Spektrums: Hochliteratur – definiert als Werke, die auf der Auswahlliste von Literaturpreisen standen – und Heftromanen, massenproduzierten Erzählwerken, die zumeist über den Zeitschriftenhandel vertrieben werden und früher abwertend als „Romane der Unterschicht” (Nusser 1981) bezeichnet wurden. Unsere These ist, dass sich diese Literaturtypen hinsichtlich ihrer Erzählweise unterscheiden, und sich dies in den verwendeten Wiedergabeformen niederschlägt. Der Fokus der Untersuchung liegt auf der Dichotomie zwischen direkter und nicht-direkter Wiedergabe, die schon in der klassischen Rhetorik aufgemacht wurde.
We present recognizers for four very different types of speech, thought and writing representation (STWR) for German texts. The implementation is based on deep learning with two different customized contextual embeddings, namely FLAIR embeddings and BERT embeddings. This paper gives an evaluation of our recognizers with a particular focus on the differences in performance we observed between those two embeddings. FLAIR performed best for direct STWR (F1=0.85), BERT for indirect (F1=0.76) and free indirect (F1=0.59) STWR. For reported STWR, the comparison was inconclusive, but BERT gave the best average results and best individual model (F1=0.60). Our best recognizers, our customized language embeddings and most of our test and training data are freely available and can be found via www.redewiedergabe.de or at github.com/redewiedergabe.