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Although the N400 was originally discovered in a paradigm designed to elicit a P300 (Kutas and Hillyard, 1980), its relationship with the P300 and how both overlapping event-related potentials (ERPs) determine behavioral profiles is still elusive. Here we conducted an ERP (N = 20) and a multiple-response speed-accuracy tradeoff (SAT) experiment (N = 16) on distinct participant samples using an antonym paradigm (The opposite of black is white/nice/yellow with acceptability judgment). We hypothesized that SAT profiles incorporate processes of task-related decision-making (P300) and stimulus-related expectation violation (N400). We replicated previous ERP results (Roehm et al., 2007): in the correct condition (white), the expected target elicits a P300, while both expectation violations engender an N400 [reduced for related (yellow) vs. unrelated targets (nice)]. Using multivariate Bayesian mixed-effects models, we modeled the P300 and N400 responses simultaneously and found that correlation between residuals and subject-level random effects of each response window was minimal, suggesting that the components are largely independent. For the SAT data, we found that antonyms and unrelated targets had a similar slope (rate of increase in accuracy over time) and an asymptote at ceiling, while related targets showed both a lower slope and a lower asymptote, reaching only approximately 80% accuracy. Using a GLMM-based approach (Davidson and Martin, 2013), we modeled these dynamics using response time and condition as predictors. Replacing the predictor for condition with the averaged P300 and N400 amplitudes from the ERP experiment, we achieved identical model performance. We then examined the piecewise contribution of the P300 and N400 amplitudes with partial effects (see Hohenstein and Kliegl, 2015). Unsurprisingly, the P300 amplitude was the strongest contributor to the SAT-curve in the antonym condition and the N400 was the strongest contributor in the unrelated condition. In brief, this is the first demonstration of how overlapping ERP responses in one sample of participants predict behavioral SAT profiles of another sample. The P300 and N400 reflect two independent but interacting processes and the competition between these processes is reflected differently in behavioral parameters of speed and accuracy.
This paper aims at investigating the usage of present subjunctive (Konjunktiv I), which is traditionally labelled as a feature of standard written language and therefore as typically occurring in communication genres based on it such as press texts and reporting, in everyday spoken German. Through an analysis of corpus data performed according to theory and method of Interactional Linguistics and encompassing private, institutional and public interactional domains, the paper will show how this particular verb form expresses different epistemic stances according to its syntactic embedment.
This paper focuses on so called syntactic projection phenomena in the German language. This term from the German Gesprächsforschung is used to define the fact that an utterance or part of it foreshadows another one. This paper aims at pointing out how such projection phenomena are consciously exploited for rhethorical purposes. This will be observed on the basis of excerpts from the Stuttgart 21 mediation talks. The linguistic analysis carried out in this paper will focus on syntactic projection phenomena involving the use of causal adverbial connectives deshalb and deswegen.
In this paper, we describe a data processing pipeline used for annotated spoken corpora of Uralic languages created in the INEL (Indigenous Northern Eurasian Languages) project. With this processing pipeline we convert the data into a loss-less standard format (ISO/TEI) for long-term preservation while simultaneously enabling a powerful search in this version of the data. For each corpus, the input we are working with is a set of files in EXMARaLDA XML format, which contain transcriptions, multimedia alignment, morpheme segmentation and other kinds of annotation. The first step of processing is the conversion of the data into a certain subset of TEI following the ISO standard ’Transcription of spoken language’ with the help of an XSL transformation. The primary purpose of this step is to obtain a representation of our data in a standard format, which will ensure its long-term accessibility. The second step is the conversion of the ISO/TEI files to a JSON format used by the “Tsakorpus” search platform. This step allows us to make the corpora available through a web-based search interface. As an addition, the existence of such a converter allows other spoken corpora with ISO/TEI annotation to be made accessible online in the future.
As the Web ought to be considered as a series of sources rather than as a source in itself, a problem facing corpus construction resides in meta-information and categorization. In addition, we need focused data to shed light on particular subfields of the digital public sphere. Blogs are relevant to that end, especially if the resulting web texts can be extracted along with metadata and made available in coherent and clearly describable collections.
Speech planning is a sophisticated process. In dialog, it regularly starts in overlap with an incoming turn by a conversation partner. We show that planning spoken responses in overlap with incoming turns is associated with higher processing load than planning in silence. In a dialogic experiment, participants took turns with a confederate describing lists of objects. The confederate’s utterances (to which participants responded) were pre-recorded and varied in whether they ended in a verb or an object noun and whether this ending was predictable or not. We found that response planning in overlap with sentence-final verbs evokes larger task-evoked pupillary responses, while end predictability had no effect. This finding indicates that planning in overlap leads to higher processing load for next speakers in dialog and that next speakers do not proactively modulate the time course of their response planning based on their predictions of turn endings. The turn-taking system exerts pressure on the language processing system by pushing speakers to plan in overlap despite the ensuing increase in processing load.
Since 2013 representatives of several French and German CMC corpus projects have developed three customizations of the TEI-P5 standard for text encoding in order to adapt the encoding schema and models provided by the TEI to the structural peculiarities of CMC discourse. Based on the three schema versions, a 4th version has been created which takes into account the experiences from encoding our corpora and which is specifically designed for the submission of a feature request to the TEI council. On our poster we would present the structure of this schema and its relations (commonalities and differences) to the previous schemas.
Most authors agree that modal particles - a dass of function words widely considered characteristic of Modem German - cannot receive prosodic stress, though the reasons for this restriction have not yet been satisfactorily explained. This paper argues that unstressability follows from the general contribution of modal particles to compositional utterance meaning, which requires them to take scope over focus-background structures. Form and function of modal particle meanings are modelled and illustrated for five representative examples - the particles wohl, ja, eigentlich, eben and halt. It is argued that these as well as other particles, whenever they occur under prosodic stress, cannot preserve the meaning nor the syntactic behaviour of modal particles. All instances of stressed particles in German must therefore be categorized in other functional classes.
This contribution presents a quantitative approach to speech, thought and writing representation (ST&WR) and steps towards its automatic detection. Automatic detection is necessary for studying ST&WR in a large number of texts and thus identifying developments in form and usage over time and in different types of texts. The contribution summarizes results of a pilot study: First, it describes the manual annotation of a corpus of short narrative texts in relation to linguistic descriptions of ST&WR. Then, two different techniques of automatic detection – a rule-based and a machine learning approach – are described and compared. Evaluation of the results shows success with automatic detection, especially for direct and indirect ST&WR.
In this paper, we present our work-inprogress to automatically identify free indirect representation (FI), a type of thought representation used in literary texts. With a deep learning approach using contextual string embeddings, we achieve f1 scores between 0.45 and 0.5 (sentence-based evaluation for the FI category) on two very different German corpora, a clear improvement on earlier attempts for this task. We show how consistently marked direct speech can help in this task. In our evaluation, we also consider human inter-annotator scores and thus address measures of certainty for this difficult phenomenon.
Nearly all of the very large corpora of English are “static”, which allows a wide range of one-time, pre-processed data, such as collocates. The challenge comes with large “dynamic” corpora, which are updated regularly, and where preprocessing is much more difficult. This paper provides an overview of the NOW corpus (News on the Web), which is currently 8.2 billion words in size, and which grows by about 170 million words each month. We discuss the architecture of NOW, and provide many examples that show how data from NOW can (uniquely) be extracted to look at a wide range of ongoing changes in English.
We propose a Cross-lingual Encoder-Decoder model that simultaneously translates and generates sentences with Semantic Role Labeling annotations in a resource-poor target language. Unlike annotation projection techniques, our model does not need parallel data during inference time. Our approach can be applied in monolingual, multilingual and cross-lingual settings and is able to produce dependencybased and span-based SRL annotations. We benchmark the labeling performance of our model in different monolingual and multilingual settings using well-known SRL datasets. We then train our model in a cross-lingual setting to generate new SRL labeled data. Finally, we measure the effectiveness of our method by using the generated data to augment the training basis for resource-poor languages and perform manual evaluation to show that it produces high-quality sentences and assigns accurate semantic role annotations. Our proposed architecture offers a flexible method for leveraging SRL data in multiple languages.
In an earlier publication it was claimed that there is no useful relationship between Swahili-English dictionary look-up frequencies and the occurrence frequencies for the same wordforms in Swahili-English corpora, at least not beyond the top few thousand wordforms. This result was challenged using data for German by a different team of researchers using an improved methodology. In the present article the original Swahili-English data is revisited, using ten years’ worth of it rather than just two, and using the improved methodology. We conclude that there is indeed a positive relationship. In addition, we show that online dictionary look-up behaviour is remarkably similar across languages, even when, as in our case, one is dealing with languages from very dissimilar language families. Furthermore, online dictionaries turn out to have minimum look-up success rates, below which they simply cannot go. These minima are language-sensitive and vary depending on the regularity of the searched-for entries, but are otherwise constant no matter the size of randomly sampled dictionaries. Corpus-informed sampling always improves on any random method. Lastly, from the point of view of the graphical user interface, we argue that the average user of an online bilingual dictionary is better served with a single search box, rather than separate search boxes for each dictionary side.
How do people communicate in mobile settings of interaction? How does mobility affect the way we speak? How does mobility exert influence on the manner in which talk itself is consequential for how we move in space? Recently, questions of this sort have attracted increasing attention in the human and social sciences. This Special Issue contributes to the emerging body of studies on mobility and talk by inspecting an ordinary and ubiquitous phenomenon in which communication among mobile participants is paramount: participation in traffic. This editorial presents previous work on mobility in natural settings, as carried out by interactionally oriented researchers. It also shows how the investigation into traffic participation adds new perspectives to research on language and communication.
Статтю присвячено дослідженню комунікативних невдач у мовленнєвому жанрі відеоінтерв’ю крізь призму української національної ідентичності. Визначено тематику, типи і жанрово-мовну специфіку українського відеоінтерв’ю як зразка діалогічного мовлення. Встановлено специфіку комунікативних невдач у цьому жанрі (зі спортсменами, політиками і культурними діячами) з огляду на позиції комунікантів, структурні рівні досліджуваного жанру та максими спілкування.
The article deals with communicative failures of journalists in “YouTube” celebrity video interviews in the Ukrainian and German linguacultures from the point of view of social interaction and the theory of speech genres at all structural levels of the communicative genre construction, establishing common and distinctive features in both linguacultures. The analysis made it possible to conclude that behind a language (speech) failure there is a violation caused by a journalist, a respondent, or an external noise.