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The present thesis introduces KoralQuery, a protocol for the generic representation of queries to linguistic corpora. KoralQuery defines a set of types and operations which serve as abstract representations of linguistic entities and configurations. By combining these types and operations in a nested structure, the protocol may express linguistic structures of arbitrary complexity. It achieves a high degree of neutrality with regard to linguistic theory, as it provides flexible structures that allow for the setting of certain parameters to access several complementing and concurrent sources and layers of annotation on the same textual data. JSON-LD is used as a serialisation format for KoralQuery, which allows for the well-defined and normalised exchange of linguistic queries between query engines to promote their interoperability. The automatic translation of queries issued in any of three supported query languages to such KoralQuery serialisations is the second main contribution of this thesis. By employing the introduced translation module, query engines may also work independently of particular query languages, as their backend technology may rely entirely on the abstract KoralQuery representations of the queries. Thus, query engines may provide support for several query languages at once without any additional overhead. The original idea of a general format for the representation of linguistic queries comes from an initiative called Corpus Query Lingua Franca (CQLF), whose theoretic backbone and practical considerations are outlined in the first part of this thesis. This part also includes a brief survey of three typologically different corpus query languages, thus demonstrating their wide variety of features and defining the minimal target space of linguistic types and operations to be covered by KoralQuery.
The task-oriented and format-driven development of corpus query systems has led to the creation of numerous corpus query languages (QLs) that vary strongly in expressiveness and syntax. This is a severe impediment for the interoperability of corpus analysis systems, which lack a common protocol. In this paper, we present KoralQuery, a JSON-LD based general corpus query protocol, aiming to be independent of particular QLs, tasks and corpus formats. In addition to describing the system of types and operations that Koral- Query is built on, we exemplify the representation of corpus queries in the serialized format and illustrate use cases in the KorAP project.
Hierarchical predictive coding has been identified as a possible unifying principle of brain function, and recent work in cognitive neuroscience has examined how it may be affected by age–related changes. Using language comprehension as a test case, the present study aimed to dissociate age-related changes in prediction generation versus internal model adaptation following a prediction error. Event-related brain potentials (ERPs) were measured in a group of older adults (60–81 years; n = 40) as they read sentences of the form “The opposite of black is white/yellow/nice.” Replicating previous work in young adults, results showed a target-related P300 for the expected antonym (“white”; an effect assumed to reflect a prediction match), and a graded N400 effect for the two incongruous conditions (i.e. a larger N400 amplitude for the incongruous continuation not related to the expected antonym, “nice,” versus the incongruous associated condition, “yellow”). These effects were followed by a late positivity, again with a larger amplitude in the incongruous non-associated versus incongruous associated condition. Analyses using linear mixed-effects models showed that the target-related P300 effect and the N400 effect for the incongruous non-associated condition were both modulated by age, thus suggesting that age-related changes affect both prediction generation and model adaptation. However, effects of age were outweighed by the interindividual variability of ERP responses, as reflected in the high proportion of variance captured by the inclusion of by-condition random slopes for participants and items. We thus argue that – at both a neurophysiological and a functional level – the notion of general differences between language processing in young and older adults may only be of limited use, and that future research should seek to better understand the causes of interindividual variability in the ERP responses of older adults and its relation to cognitive performance.
One was a distinguished natural scientist and engineer, the other a self-taught scientist and vilified as a conman: Christian Gottlieb Kratzenstein (1723–1795) and Wolfgang von Kempelen (1734–1804). Some of the former’s postula-tions on human physiology and articulation of speech proved wrong in later years. Most of the latter’s theories are considered applicable even today. The perhaps most contrasting approaches to speech synthesis during the 18th century are linked to their names. There are many essential differences between their approaches which show that these two researchers were not only representatives of different schools of thought, but also representatives of two different scientific eras. A speculative and philosophical approach on the one hand versus an empirical and logical approach on the other hand. Both Kratzenstein and Kempelen published books on their research. But while the “Tentamen” [4] of the physician Kratzen-stein remains rather vague and imprecise in its descriptions of vowel production and synthesis, the “Mechanismus” [8] of the engineer Kempelen shows much more precision and correctness in almost every respect of human speech and lan-guage. The goal of this paper is to discuss the differences between these two con-temporaneous researchers on speech synthesis and to compare their theories with present-days findings.
Mit den Methoden der Interaktionalen Linguistik und der Konversationsanalyse untersucht die vorliegende Arbeit syntaktische Ko-Konstruktionen im gesprochenen Deutsch, wobei der Fokus auf Vervollständigungen eines zweiten Sprechers vor einem möglichen syntaktischen Abschlusspunkt liegt. Auf der Basis von 199 Ko-Konstruktionen aus informellen Interviews und Tischgesprächen leistet die Arbeit eine erste umfassende Analyse der gemeinsamen Konstruktion einer syntaktischen Gestalt durch zwei Sprecher im Deutschen.
Die Struktur der Ko-Konstruktionen wird in einem ersten Schritt über die Basisoperationen der Online-Syntax, Projektion und Retraktion, beschrieben. Im Fokus steht hier die Frage, an welchen Projektionen sich der zweite Sprecher orientiert, wobei sowohl syntaktische und prosodische als auch semanto-pragmatische Aspekte in die Analyse miteinbezogen werden. In einem zweiten Schritt wird die zeitliche und sequenzielle Organisation der Ko-Konstruktionen detailliert herausgearbeitet. Ein Schwerpunkt liegt hier auf einer genauen Darstellung und Analyse der verschiedenen Handlungsoptionen des ersten Sprechers nach der ko-konstruierten Vervollständigung.
Mit traditionellen Methoden der Narratologie ist es nur möglich, eine begrenzte Menge von (meist kanonischen) Texten zu untersuchen. Computer hingegen können große Textmengen bewältigen und über die breitere empirische Basis einen neuen Blick auf das literarischen Schaffen eröffnen. Dazu ist es jedoch notwendig, narratologische Konzepte auch automatisch erfassbar zu machen. Die vorliegende Studie untersucht, wie ein etabliertes Phänomen des Erzählens – die Wiedergabe von Rede, Gedanken und Geschriebenem in narrativen Texten – mit Hilfe automatischer Methoden identifiziert werden kann. Auf der Basis narratologischer Forschungsliteratur wird zunächst ein Annotationsystem für Redewiedergabeformen entwickelt und auf ein Beispielkorpus von deutschsprachigen Erzähltexten angewendet. Anschließend werden Methoden zur automatischen Erkennung und deren Ergebnisse vorgestellt. Prototypen der beschriebenen Redewiedergabeerkenner sind online frei verfügbar. Die Studie liefert konkrete Ansätze für die automatische Erkennung von Redewiedergabe und demonstriert zugleich Strategien für die Nutzung von Methoden der Digital Humanities in der Narratologie.