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Although there is a growing interest of policy makers in higher education issues (especially on an international scale), there is still a lack of theoretically well-grounded comparative analyses of higher education policy. Even broadly discussed topics in higher education research like the potential convergence of European higher education systems in the course of the Bologna Process suffer from a thin empirical and comparative basis. This paper aims to deal with these problems by addressing theoretical questions concerning the domestic impact of the Bologna Process and the role national factors play in determining its effects on cross-national policy convergence. It develops a distinct theoretical approach for the systematic and comparative analysis of cross-national policy convergence. In doing so, it relies upon insights from related research areas — namely literature on Europeanization as well as studies dealing with cross-national policy convergence.
MRI data of German vowels and consonants was acquired for 9 speakers. In this paper tongue contours for the vowels were analyzed using the three-mode factor analysis technique PARAFAC. After some difficulties, probably related to what constitutes an adequate speaker sample for this three-mode technique to work, a stable two-factor solution was extracted that explained about 90% of the variance. Factor 1 roughly captured the dimension low back to high front; Factor 2 that from mid front to high back. These factors are compared with earlier models based on PARAFAC. These analyses were based on midsagittal contours; the paper concludes by illustrating from coronal and axial sections how non-midline information could be incorporated into this approach.
Distributional models of word use constitute an indispensable tool in corpus based lexicological research for discovering paradigmatic relations and syntagmatic patterns (Belica et al. 2010). Recently, word embeddings (Mikolov et al. 2013) have revived the field by allowing to construct and analyze distributional models on very large corpora. This is accomplished by reducing the very high dimensionality of word cooccurrence contexts, the size of the vocabulary, to few dimensions, such as 100-200. However, word use and meaning can vary widely along dimensions such as domain, register, and time, and word embeddings tend to represent only the most prevalent meaning. In this paper we thus construct domain specific word embeddings to allow for systematically analyzing variations in word use. Moreover, we also demonstrate how to reconstruct domain specific co-occurrence contexts from the dense word embeddings.
Korpora sind – als idealerweise digital verfüg- und auswertbare Sammlungen von Texten – eine wertvolle empirische Grundlage linguistischer Studien. Eigene Korpora aufzubauen ist, je nach Sprachausschnitt, mit unterschiedlichen Herausforderungen verbunden. Zu allen Texten sollten Metadaten zu den Textentstehungsbedingungen (Zeit, Quelle usw.) erhoben werden, um diese als Variablen in Auswertungen einbeziehen zu können. Andere Informationen wie etwa die Themenzugehörigkeit (oder Annotationen auch unterhalb der Textebene) sind auch hilfreich, in vielerlei Hinsicht aber schwieriger pauschal taxonomisch vorzugeben, geschweige denn, operationell zu ermitteln. Jenseits der »materiellen« Verfügbarkeit der Texte und der technischen Aufbereitung sind es das Urheberrecht, vor allem Lizenz- bzw. Nutzungsrechte, sowie ethische Verantwortung und Persönlichkeitsrechte, die beachtet werden müssen, auch um zu gewährleisten, dass die Daten für die Reproduktion der Studien Dritten rechtssicher zugänglich gemacht werden dürfen. Bevor für ein Vorhaben ein neues Korpus aufgebaut wird, sollte deshalb am besten geprüft werden, ob nicht ein geeignetes bereits zur Verfügung steht. Wenn ein Korpus aufgebaut wird, sollte für eine nachhaltige Aufbewahrung und Zugänglichmachung gesorgt und die Existenz an geeigneter Stelle dokumentiert werden.
In HDK-1 und in HDK-2 werden Perfektpartizipien wie angenommen und vorausgesetzt in der ‚absoluten‘ Verwendung ohne Auxiliar als vollständig grammatikalisierte Konnektoren mit konditionaler Semantik behandelt. Zwar werden sie von semantisch unterschiedlichen Verben gebildet, in der Verwendung als Konnektor lassen sich aber zumindest hinsichtlich der Wahrheitsbedingungen kaum semantische Unterschiede mehr erkennen. Deutliche Unterschiede zeigen sich aber im Sprachgebrauch: Basierend auf einer groß angelegten Korpusstudie wird gezeigt, dass sich angenommen und vorausgesetzt stark unterscheiden hinsichtlich a) ihrer Präferenz für die Einbettung von V2- vs. dass-Nebensätzen, b) des präferierten Verbmodus im Nebensatz, c) der topologischen Präferenz des untergeordneten Satzes sowie d) der Kookkurrenz mit anderen Ausdrücken. Es wird versucht, diese Unterschiede mit einem pragmatisch-funktionalen Ansatz zu erklären.
Dieser Artikel analysiert am Beispiel eines Racletteessens unter Freunden, wie innerhalb einer langen Sequenz das Warten auf den Beginn des Essens strukturiert wird. Während der fast 50 Minuten, die zwischen der Ankunft der ersten Gäste sowie dem Beginn des Essens vergehen, orientieren sich die Teilnehmer auf unterschiedliche Weise zum Warten als Aktivität. Das sukzessive Eintreffen der Gäste führt jeweils zu Eröffnungssequenzen innerhalb dieser Wartezeit. Anhand von Auszügen dieser Zeitspanne verfolgt die Analyse, wie sich die Teilnehmer zu dieser Zeitlichkeit des Wartens und (Noch-nicht-)Beginnens orientieren und wie sie den Anfang des Essens gemeinsam konstruieren.
We continue the study of the reproducibility of Propp’s annotations from Bod et al. (2012). We present four experiments in which test subjects were taught Propp’s annotation system; we conclude that Propp’s system needs a significant amount of training, but that with sufficient time investment, it can be reliably trained for simple tales.
Since the beginning of the Covid-19 pandemic, about 2000 new lexical units have entered the German lexicon. These concern a multitude of coinings and word formations (Kuschelkontakt, rumaerosolen, pandemüde) as well as lexical borrowings mainly from English (Lockdown, Hotspot, Superspreader). In a special way, these neologisms function as keywords and lexical indicators sketching the development of the multifaceted corona discourse in Germany. They can be detected systematically by corpus-linguistic investigations of reports and debates in contemporary public communication. Keyword analyses not only exhibit new vocabulary, they also reveal discursive foci, patterns of argumentation and topicalisations within the diverse narratives of the discourse. With the help of quickly established and dominant neologisms, this paper will outline typical contexts and thematic references, but it will also identify speakers' attitudes and evaluations.
Theateraufführungen sind ohne Zuschauer nicht denkbar. Zugleich erweisen sich Proben aber als öffentlichkeitsabgeschirmte und intime Vorgänge, da eine (zu frühe) Orientierung an möglichen Publikums-Effekten den kreativen Prozess stört. Auf der Grundlage von über 30 Stunden Videoaufnahmen von Theaterproben zeige ich an ausgewählten Ausschnitten, wie Theatermachende sich sprachlich und körperlich im Probenprozess auf das Publikum beziehen, wie dies interaktiv realisiert wird und welche Rückschlüsse das auf die Weisen der Publikumskonstruktion im Kontext von Proben zulässt.
Antonymy is a relation of lexical opposition which is generally considered to involve (i) the presence of a scale along which a particular property may be graded, and hence both (ii) gradability of the corresponding lexical items and (iii) typical entailment relations. Like other types of lexical opposites, antonyms typically differ only minimally: while denoting opposing poles on the relevant dimension of difference, they are similar with respect to other components of meaning. This paper presents examples of antonymy from the domain of speech act verbs which either lack some of these typical attributes or show problems in the application of these. It discusses several different proposals for the classification of these atypical examples.
Repeating the movements associated with activities such as drawing or sports typically leads to improvements in kinematic behavior: these movements become faster, smoother, and exhibit less variation. Likewise, practice has also been shown to lead to faster and smoother movement trajectories in speech articulation. However, little is known about its effect on articulatory variability. To address this, we investigate the extent to which repetition and predictability influence the articulation of the frequent German word “sie” [zi] (they). We find that articulatory variability is proportional to speaking rate and the duration of [zi], and that overall variability decreases as [zi] is repeated during the experiment. Lower variability is also observed as the conditional probability of [zi] increases, and the greatest reduction in variability occurs during the execution of the vocalic target of [i]. These results indicate that practice can produce observable differences in the articulation of even the most common gestures used in speech.
HMMs are the dominating technique used in speech recognition today since they perform well in overall phone recognition. In this paper, we show the comparison of HMM methods and machine learning techniques, such as neural networks, decision trees and ensemble classifiers with boosting and bagging in the task of articulatory-acoustic feature classification. The experimental results show that HMM methods work well for the classification of such features as vocalic. However, decision tree and bagging outperform HMMs for the fricative classification task since the data skewness is much higher than for the feature vocalic classification task. This demonstrates that HMMs do not perform as well as decision trees and bagging in highly skewed data settings.
Precise multimodal studies require precise synchronisation between audio and video signals. However, raw audio and audio from video recordings can be out of sync for several reasons. In order to re-synchronise them, a dynamic programming (DP) approach is presented here. Traditionally, DP is performed on the rectangular distance matrix comparing each value in signal A with each value in signal B. Previous work limited the search space using for example the Sakoe Chiba Band (Sakoe and Chiba, 1978). However, the overall space of the distance matrix remains identical. Here, a tunnel matrix and its according DP-algorithm are presented. The matrix contains merely the computed distance of two signals to a pre-specified bandwidth and the computational cost is equally reduced. An example implementation demonstrates the functionality on artificial data and on data from real audio and video recordings.
„Actual words are of theoretical interest” (Audring 2021: 3). Unter Zugrundelegung dieser gebrauchsbasierten Prämisse geht der vorliegende Beitrag der Frage nach, wie sich die Nominalkomposition im Deutschen auf der Basis sprachlicher Massendaten als Konstruktionsfamilie, d.h. als ein hierarchisches Netzwerk von Konstruktionen unterschiedlichen Abstraktionsgrads, beschreiben lässt. Der Beitrag knüpft in theoretischer Hinsicht an Booijs (2010) „Construction Morphology” an, geht jedoch insofern über diese hinaus, als versucht wird, deren Grundannahmen auch auf automatisch erhobene sprachliche Massendaten anzuwenden. Konkret wird mit einem Inventar von rund 185.000 Zusammensetzungen aus zwei simplizischen Nomen gearbeitet, die systematisch aus dem Deutschen Referenzkorpus (DeReKo) (vgl. Leibniz-Institut für Deutsche Sprache 2007) extrahiert und im Anschluss (semi)automatisch weiterverarbeitet wurden.
Automatic recognition of speech, thought, and writing representation in German narrative texts
(2013)
This article presents the main results of a project, which explored ways to recognize and classify a narrative feature—speech, thought, and writing representation (ST&WR)—automatically, using surface information and methods of computational linguistics. The task was to detect and distinguish four types—direct, free indirect, indirect, and reported ST&WR—in a corpus of manually annotated German narrative texts. Rule-based as well as machine-learning methods were tested and compared. The results were best for recognizing direct ST&WR (best F1 score: 0.87), followed by indirect (0.71), reported (0.58), and finally free indirect ST&WR (0.40). The rule-based approach worked best for ST&WR types with clear patterns, like indirect and marked direct ST&WR, and often gave the most accurate results. Machine learning was most successful for types without clear indicators, like free indirect ST&WR, and proved more stable. When looking at the percentage of ST&WR in a text, the results of machine-learning methods always correlated best with the results of manual annotation. Creating a union or intersection of the results of the two approaches did not lead to striking improvements. A stricter definition of ST&WR, which excluded borderline cases, made the task harder and led to worse results for both approaches.
Feminine forms of job titles raise great interest in many countries. However, it is still unknown how they shape stereotypical impressions on warmth and competence dimensions among female and male listeners. In an experiment with fictitious job titles men perceived women described with feminine job titles as significantly less warm and marginally less competent than women with masculine job titles, which led to lower willingness to employ them. No such effects were observed among women.