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This presentation deals with collaborative turn-sequences (Lerner 2004), a syntactically coherent unit of talk that is jointly formulated by at least two speakers, in Czech and German everyday conversations. Based on conversation analysis (e.g., Schegloff 2007) and a multimodal approach to social interaction (e.g., Deppermann/Streeck 2018), we aim at comparing recurrent patterns and action types within co-constructional sequences in both languages. The practice of co-constructing turns-at-talk has been described for typologically different languages, especially for English (e.g., Lerner 1996, 2004), but also for languages such as Japanese (Hayashi 2003) or Finnish (Helasvuo 2004). For German, various forms and functions of co-constructions have already been investigated (e.g., Brenning 2015); for Czech, a detailed, interactionally based description is still pending (but see some initial observations in, e.g., Hoffmannová/Homoláč/Mrázková (eds.) 2019). Although the existence of co-constructions in different languages points to a cross-linguistic conversational practice, few explicitly comparative studies exist (see, e.g., Lerner/Takagi 1999, for English and Japanese). The language pair Czech-German has mainly been studied with respect to language contact and without specifically considering spoken language or complex conversational sequences (e.g., Nekula/Šichová/Valdrová 2013). Therefore, our second aim is to sketch out a first comparison of co-constructional sequences in German and Czech, thereby contributing to the growing field of comparative and cross-linguistic studies within conversation analysis (e.g., Betz et al. (eds.) 2021; Dingemanse/Enfield 2015; Sidnell (ed.) 2009). More specifically, we will present three main sequential patterns of co-constructional sequences, focusing on the type of action a second speaker carries out by completing a first speaker’s possibly incomplete turn-at-talk, and on how the initial speaker then responds to
this suggested completion (Lerner 2004). Excerpts from video recordings of Czech and German ordinary conversations will illustrate these recurrent co-constructional sequence types, i.e., offering help during word searches (see example 1 above), displaying understanding, or claiming independent knowledge. The third objective of this paper is to underline the participants’ orientation to similar interactional problems, solved by specific syntactic and/or lexical formats in Czech and German. Considering the more recent focus on the embodied dimension of co-constructional practices (e.g., Dressel 2020), we will also investigate the multimodal formatting of a started utterance as more or less “permeable” (Lerner 1996) for co-participant completion, the participants’ mutual embodied orientation, and possible embodied responses to others’ turn-completions (such as head nods or eyebrow flashes, cf. De Stefani 2021). More generally, this contribution reflects on the possibilities and challenges of a cross-linguistic comparison of complex multimodal sequences.
It is well known that the distribution of lexical and grammatical patterns is size- and register-sensitive (Biber 1986, and later publications). This fact alone presents a challenge to many corpus-oriented linguistic studies focusing on a single language. When it comes to cross-linguistic studies using corpora, the challenge becomes even greater due to the lack of high-quality multilingual corpora (Kupietz et al. 2020; Kupietz/Trawiński 2022), which are comparable with respect to the size and the register. That was the motivation for the creation of the European Reference Corpus EuReCo, an initiative started in 2013 at the Leibniz Institute for the German Language (IDS) together with several European partners (Kupietz et al. 2020). EuReCo is an emerging federated corpus, with large virtual comparable corpora across various languages and with an infrastructure supporting contrastive research. The core of the infrastructure is KorAP (Diewald et al. 2016), a scalable open-source platform supporting the analysis and visualisation of properties of texts annotated by multiple and potentially conflicting information layers, and supporting several corpus query languages. Until recently, EuReCo consisted of three monolingual subparts: the German Reference Corpus DeReKo (Kupietz et al. 2018), the Reference Corpus of Contemporary Romanian Language (Barbu Mititelu/Tufiş/Irimia 2018), and the Hungarian National Corpus (Váradi 2002). The goal of the present submission is twofold. On the one hand, it reports about the new component of EuReCo: a sample of the National Corpus of Polish (Przepiórkowski et al. 2010). On the other hand, it presents the results of a new pilot study using the newly extended EuReCo. This pilot study investigates selected Polish collocations involving light verbs and their prepositional / nominal complements (Fig. 1) and extends the collocation analyses of German, Romanian and Hungarian (Fig. 2) discussed in Kupietz/Trawiński (2022).
This conference booklet provides information about 10th International Contrastive Linguistics Conference (ICLC-10) that took place in Mannheim, Germany, from 18 to 21 July 2023. It contains
– a description of the conference aims,
– details on the conference venue,
– information on committees,
– the conference program,
– the abstracts of the keynotes, oral and poster presentations, and
– an author index.
Computational language models (LMs), most notably exemplified by the widespread success of OpenAI's ChatGPT chatbot, show impressive performance on a wide range of linguistic tasks, thus providing cognitive science and linguistics with a computational working model to empirically study different aspects of human language. Here, we use LMs to test the hypothesis that languages with more speakers tend to be easier to learn. In two experiments, we train several LMs—ranging from very simple n-gram models to state-of-the-art deep neural networks—on written cross-linguistic corpus data covering 1293 different languages and statistically estimate learning difficulty. Using a variety of quantitative methods and machine learning techniques to account for phylogenetic relatedness and geographical proximity of languages, we show that there is robust evidence for a relationship between learning difficulty and speaker population size. However, contrary to expectations derived from previous research, our results suggest that languages with more speakers tend to be harder to learn.
One of the fundamental questions about human language is whether all languages are equally complex. Here, we approach this question from an information-theoretic perspective. We present a large scale quantitative cross-linguistic analysis of written language by training a language model on more than 6500 different documents as represented in 41 multilingual text collections consisting of ~ 3.5 billion words or ~ 9.0 billion characters and covering 2069 different languages that are spoken as a native language by more than 90% of the world population. We statistically infer the entropy of each language model as an index of what we call average prediction complexity. We compare complexity rankings across corpora and show that a language that tends to be more complex than another language in one corpus also tends to be more complex in another corpus. In addition, we show that speaker population size predicts entropy. We argue that both results constitute evidence against the equi-complexity hypothesis from an information-theoretic perspective.
Kontrastiv-multilingual angelegte empirische Studien erfordern eine vergleichbare Datengrundlage. Je nachdem, welche Forschungsfragen im Zentrum der sprachvergleichenden Untersuchungen stehen, bieten sich entweder Parallelkorpora oder vergleichbare einzelsprachliche Korpora als Datengrundlage an. Dieser Beitrag verfolgt hauptsächlich das Ziel, die Herausforderungen aufzuzeigen, die die Arbeit mit vergleichbaren Korpora im multilingualen Sprachvergleich aufwirft. Dabei soll u.a. das Prinzip der Vergleichbarkeit von Korpora thematisiert und methodologische Vorschläge für konkrete empirisch angelegte sprachvergleichende Analysen vorgelegt werden. Die Möglichkeiten und Grenzen der empirisch basierten quantitativen und qualitativen Analysearbeit werden durch die Präsentation einiger exemplarischer Forschungsfragen und -ergebnisse aufgezeigt. Einige Desiderata für zukünftige korpusbasierte Studien auf der Basis von vergleichbaren Korpora im multilingualen Raum schließen den Beitrag ab.
Konvergenz und Divergenz
(2021)
This paper reports on recent developments within the European Reference Corpus EuReCo, an open initiative that aims at providing and using virtual and dynamically definable comparable corpora based on existing national, reference or other large corpora. Given the well-known shortcomings of other types of multilingual corpora such as parallel/translation corpora (shining-through effects, over-normalization, simplification, etc.) or web-based comparable corpora (covering only web material), EuReCo provides a unique linguistic resource offering new perspectives for fine-grained contrastive research on authentic cross-linguistic data, applications in translation studies and foreign language teaching and learning.
Dieser Beitrag stellt ein neues, im Aufbau befindliches Parallelkorpus vor: Das ‚Parallel European Corpus of Informal Interaction‘ (PECII). Zunächst wird der Bedarf nach besser vergleichbaren Daten fur die sprachübergreifende Erforschung natürlichen sprachlichen Handelns in der sozialen Interaktion begründet. Wir diskutieren Fragen der Vergleichbarkeit von Episoden natürlicher sozialer Interaktion, und die methodologischen Herausforderungen, die Ansprüche an ein Korpus natürlicher Sprachdaten mit dem Wunsch nach vergleichbaren Daten in Einklang zu bringen. Schließlich skizzieren wir mögliche Untersuchungsansätze auf der Grundlage von PECII anhand einer laufenden Studie zur Sanktionierung von Fehlverhalten in verschiedenen Aktivitätskontexten. Zukünftig soll PECII der wissenschaftlichen Öffentlichkeit als Ressource fur die sprach- und kulturvergleichende Untersuchung sprachlichen Handelns in der sozialen Interaktion zur Verfügung stehen.