A Quantitative Framework for Specifying Underlying Representations in Child Language Acquisition

My research broadly demonstrates how quantitative approaches can be effectively leveraged for developmental research. In this dissertation, I show one quantitatively precise way to identify the nature of developing mental representations in a variety of domains; my approach utilizes the connection between a learners input, creation of a potential mental representation from that input, and evaluation with respect to the learners output. More specifically, the quantitative approach I use leverages both realistic input data and realistic output data as part of the model design and evaluation. Using modeling, we have the opportunity to concretely evaluate representational options that we would not otherwise be able to disambiguate. I demonstrate this quantitative approach with three case studies in language development: (I) the development of adjective ordering preferences, where I find that the representations that adults use to talk to children are different than the ones used to talk to other, adults, (II) immature individual syntactic category representations, where I identify precisely which immature category representation young children are likely to be using, and (III) the development of adult productive syntactic category representations, where I identify when adult category knowledge emerges in typically and atypically developing populations

A computer assisted analysis of literary text: from feature analysis to judgements of literary merit

A thesis submitted to the University of Bedfordshire in ful lment of the requirements for the degree of Doctor of PhilosophyUsing some of the tools developed mainly for authorship authentication, this study develops a toolbox of techniques towards enabling computers to detect aesthetic qualities in literature. The literature review suggests that the style markers that indicate a particular author may be adapted to show literary style that constitutes a "good" book. An initial experiment was carried out to see to what extent the computer can identify specific literary features both before and after undergoing a "corruption" of text by translating and re-translating the texts. Preliminary results were encouraging, with up to 90 per cent of the literary features being identifi ed, suggesting that literary characteristics are robust and quanti fiable. An investigation is carried out into current and historic literary criticism to determine how the texts can be classified as "good literature". Focus groups, interviews and surveys are used to pinpoint the elements of literariness as experienced by human readers that identify a text as "good". Initially identified by human experts, these elements are confirmed by the reading public. Using Classics as a genre, 100 mainly fiction texts are taken from the Gutenberg Project and ranked according to download counts from the Gutenberg website, an indicator of literary merit (Ashok et al., 2013). The texts are equally divided into five grades: four according to the download rankings and one of non- fiction texts. From these, factor analysis and mean averages determine the metrics that determine the literary quality. The metrics are qualified by a model named CoBAALT (computer-based aesthetic analysis of literary texts). CoBAALT assesses texts by Jane Austen and D. H. Lawrence and determines the degree to which they conform to the metrics for literary quality; the results demonstrate conformity with peer reviewed literary criticism

Mapping the unseen: making sense of the subjective image.

It used to be thought that photography, as a kind of automatic mapping, could provide an objective view of the world. Now we are aware of the power of framing and other interventions between what is 'out there' and what is captured in depiction. Perhaps even perception, let alone depiction, shares this subjectivity? The Sapir-Whorf hypothesis holds that different cultures actually see the world in different ways, as evidenced and influenced by concepts in their languages – though this idea has been derided, for example by Pinker. A key difficulty is that the word subjectivity is bandied about without care for its different meanings and without distinguishing the many forms it takes in the graphic image. If into this muddle we introduce the idea of interactivity, still greater confusion easily follows. The chapter brings some order to different kinds and levels of subjectivity by documenting how they are reflected in forms of graphical mapping. In the process, it becomes clear how significant is the change in media technologies from those bound by the conventional rectangles of the page and screen to media which are interactive, pervasive, multimodal, physical and social

Death-related intensifiers in the history of the English language: grammaticalisation and other proccesses of language change

The experience of death is, anthropologically, of the most genuine concern for all cultures and societies worldwide, since it marks the most extreme limits of human existence. With such an impact on our routines, it should come as no surprise that it can be effectively exploited as a source of intensification in language, perhaps even cross-linguistically. Although some studies have addressed the uses of specific intensifiers from the semantic field of death (cf. Claridge 2011 on dead and Margerie 2011 on to death), a comprehensive diachronic corpus-based study of death-related intensifiers is still missing. This dissertation, therefore, sets out to fill this gap by accounting for the semantic evolution of the intensifiers dead(ly), mortal(ly), and to death, covering from the Middle English period (1100-1500) to Present-day English

The Phenomenology of a Simple Song: Expression, Creativity, and the Recovery of Aesthetics

Abstract By placing aesthetics as art back within the phenomena of experience, this work seeks to recover philosophical aesthetics from the marginal position into which it has been relegated. Merleau-Ponty’s thought and the perception of music lay a groundwork for ontology and epistemology less conditioned by Cartesian biases. Musical thinking highlights the rich content of thought, the dimensionality of meaning, and the need to place language back within the phenomena of expression. A phenomenology of expression by way of songwriting reveals a complex creative process, a good portion of which is not transparent (neither rooted in reflective thought nor consciously determined). There emerges a notion of subjectivity and intentionality that transcends and subtends the “I” with which we ordinarily identify. The lyre of Orpheus opens the doors of the unreflective life, the aesthetic dimension, the intimacy of the world that transcends us, and the generosity of the subjectivity that subtends us

Text–to–Video: Image Semantics and NLP

When aiming at automatically translating an arbitrary text into a visual story, the main challenge consists in finding a semantically close visual representation whereby the displayed meaning should remain the same as in the given text. Besides, the appearance of an image itself largely influences how its meaningful information is transported towards an observer. This thesis now demonstrates that investigating in both, image semantics as well as the semantic relatedness between visual and textual sources enables us to tackle the challenging semantic gap and to find a semantically close translation from natural language to a corresponding visual representation. Within the last years, social networking became of high interest leading to an enormous and still increasing amount of online available data. Photo sharing sites like Flickr allow users to associate textual information with their uploaded imagery. Thus, this thesis exploits this huge knowledge source of user generated data providing initial links between images and words, and other meaningful data. In order to approach visual semantics, this work presents various methods to analyze the visual structure as well as the appearance of images in terms of meaningful similarities, aesthetic appeal, and emotional effect towards an observer. In detail, our GPU-based approach efficiently finds visual similarities between images in large datasets across visual domains and identifies various meanings for ambiguous words exploring similarity in online search results. Further, we investigate in the highly subjective aesthetic appeal of images and make use of deep learning to directly learn aesthetic rankings from a broad diversity of user reactions in social online behavior. To gain even deeper insights into the influence of visual appearance towards an observer, we explore how simple image processing is capable of actually changing the emotional perception and derive a simple but effective image filter. To identify meaningful connections between written text and visual representations, we employ methods from Natural Language Processing (NLP). Extensive textual processing allows us to create semantically relevant illustrations for simple text elements as well as complete storylines. More precisely, we present an approach that resolves dependencies in textual descriptions to arrange 3D models correctly. Further, we develop a method that finds semantically relevant illustrations to texts of different types based on a novel hierarchical querying algorithm. Finally, we present an optimization based framework that is capable of not only generating semantically relevant but also visually coherent picture stories in different styles.Bei der automatischen Umwandlung eines beliebigen Textes in eine visuelle Geschichte, besteht die größte Herausforderung darin eine semantisch passende visuelle Darstellung zu finden. Dabei sollte die Bedeutung der Darstellung dem vorgegebenen Text entsprechen. Darüber hinaus hat die Erscheinung eines Bildes einen großen Einfluß darauf, wie seine bedeutungsvollen Inhalte auf einen Betrachter übertragen werden. Diese Dissertation zeigt, dass die Erforschung sowohl der Bildsemantik als auch der semantischen Verbindung zwischen visuellen und textuellen Quellen es ermöglicht, die anspruchsvolle semantische Lücke zu schließen und eine semantisch nahe Übersetzung von natürlicher Sprache in eine entsprechend sinngemäße visuelle Darstellung zu finden. Des Weiteren gewann die soziale Vernetzung in den letzten Jahren zunehmend an Bedeutung, was zu einer enormen und immer noch wachsenden Menge an online verfügbaren Daten geführt hat. Foto-Sharing-Websites wie Flickr ermöglichen es Benutzern, Textinformationen mit ihren hochgeladenen Bildern zu verknüpfen. Die vorliegende Arbeit nutzt die enorme Wissensquelle von benutzergenerierten Daten welche erste Verbindungen zwischen Bildern und Wörtern sowie anderen aussagekräftigen Daten zur Verfügung stellt. Zur Erforschung der visuellen Semantik stellt diese Arbeit unterschiedliche Methoden vor, um die visuelle Struktur sowie die Wirkung von Bildern in Bezug auf bedeutungsvolle Ähnlichkeiten, ästhetische Erscheinung und emotionalem Einfluss auf einen Beobachter zu analysieren. Genauer gesagt, findet unser GPU-basierter Ansatz effizient visuelle Ähnlichkeiten zwischen Bildern in großen Datenmengen quer über visuelle Domänen hinweg und identifiziert verschiedene Bedeutungen für mehrdeutige Wörter durch die Erforschung von Ähnlichkeiten in Online-Suchergebnissen. Des Weiteren wird die höchst subjektive ästhetische Anziehungskraft von Bildern untersucht und "deep learning" genutzt, um direkt ästhetische Einordnungen aus einer breiten Vielfalt von Benutzerreaktionen im sozialen Online-Verhalten zu lernen. Um noch tiefere Erkenntnisse über den Einfluss des visuellen Erscheinungsbildes auf einen Betrachter zu gewinnen, wird erforscht, wie alleinig einfache Bildverarbeitung in der Lage ist, tatsächlich die emotionale Wahrnehmung zu verändern und ein einfacher aber wirkungsvoller Bildfilter davon abgeleitet werden kann. Um bedeutungserhaltende Verbindungen zwischen geschriebenem Text und visueller Darstellung zu ermitteln, werden Methoden des "Natural Language Processing (NLP)" verwendet, die der Verarbeitung natürlicher Sprache dienen. Der Einsatz umfangreicher Textverarbeitung ermöglicht es, semantisch relevante Illustrationen für einfache Textteile sowie für komplette Handlungsstränge zu erzeugen. Im Detail wird ein Ansatz vorgestellt, der Abhängigkeiten in Textbeschreibungen auflöst, um 3D-Modelle korrekt anzuordnen. Des Weiteren wird eine Methode entwickelt die, basierend auf einem neuen hierarchischen Such-Anfrage Algorithmus, semantisch relevante Illustrationen zu Texten verschiedener Art findet. Schließlich wird ein optimierungsbasiertes Framework vorgestellt, das nicht nur semantisch relevante, sondern auch visuell kohärente Bildgeschichten in verschiedenen Bildstilen erzeugen kann

Sentiment analysis and resources for informal Arabic text on social media

Online content posted by Arab users on social networks does not generally abide by the grammatical and spelling rules. These posts, or comments, are valuable because they contain users’ opinions towards different objects such as products, policies, institutions, and people. These opinions constitute important material for commercial and governmental institutions. Commercial institutions can use these opinions to steer marketing campaigns, optimize their products and know the weaknesses and/ or strengths of their products. Governmental institutions can benefit from the social networks posts to detect public opinion before or after legislating a new policy or law and to learn about the main issues that concern citizens. However, the huge size of online data and its noisy nature can hinder manual extraction and classification of opinions present in online comments. Given the irregularity of dialectal Arabic (or informal Arabic), tools developed for formally correct Arabic are of limited use. This is specifically the case when employed in sentiment analysis (SA) where the target of the analysis is social media content. This research implemented a system that addresses this challenge. This work can be roughly divided into three blocks: building a corpus for SA and manually tagging it to check the performance of the constructed lexicon-based (LB) classifier; building a sentiment lexicon that consists of three different sets of patterns (negative, positive, and spam); and finally implementing a classifier that employs the lexicon to classify Facebook comments. In addition to providing resources for dialectal Arabic SA and classifying Facebook comments, this work categorises reasons behind incorrect classification, provides preliminary solutions for some of them with focus on negation, and uses regular expressions to detect the presence of lexemes. This work also illustrates how the constructed classifier works along with its different levels of reporting. Moreover, it compares the performance of the LB classifier against Naïve Bayes classifier and addresses how NLP tools such as POS tagging and Named Entity Recognition can be employed in SA. In addition, the work studies the performance of the implemented LB classifier and the developed sentiment lexicon when used to classify other corpora used in the literature, and the performance of lexicons used in the literature to classify the corpora constructed in this research. With minor changes, the classifier can be used in domain classification of documents (sports, science, news, etc.). The work ends with a discussion of research questions arising from the research reported

Evaluation in late modern English history writing

Die vorliegende Arbeit beschäftigt sich mit der Identifikation und der Klassifikation von evaluativer Lexis in den Werken von britischen Geschichtsschreibern der Spätneuzeit. Im Fokus stehen die von den Historikern im Verlauf von 200 Jahren (ca. 1700-1914) verwendeten sprachlichen Mittel, welche zur Bewertung von historischen Ereignissen und Akteuren eingesetzt werden, und die durch die Mittel realisierten Funktionen. Zentral ist die Betrachtung von Evaluation als linguistischem Mittel der Signifikanzherstellung in neuzeitlicher englischer Geschichtsschreibung. Die Arbeit stützt sich in ihren theoretische Ansätzen u.a. auf das Appraisal Framework (Martin & White 2005) und erweitert dieses, um es unter Einsatz von sowohl korpuslinguistisch-quantitativer als auch qualitativer Methoden auf ein großes Korpus historischer Primärwerke aus dem 18.-19. Jahrhundert anzuwenden. Sie verortet sich sowohl in der historischen/diachronen Diskursforschung als auch in der korpusunterstützten Diskursanalyse (Partington et al. 2013) und liefert eine erste linguistische Beschreibung des historiographischen Registers in der wichtigen Periode seiner allmählichen Verwissenschaftlichung und Institutionalisierung. Indem sie eine interdisziplinäre Perspektive einnimmt, vermittelt diese Arbeit zwischen historischer Theoriebildung und linguistischer Theorie und Methodik.This paper is concerned with the identification and classification of evaluative lexis in the works of British historians of the Late Modern period. The focus is on the linguistic resources used by historians over the course of 200 years (c. 1700-1914) to evaluate historical events and actors, and the functions realised through these resources. Central to the study is the consideration of evaluation as a linguistic means of signaling historical significance in Late Modern English historiography. The work draws on the Appraisal Framework (Martin & White 2005) and extends it in order to apply it to a large corpus of primary historical works from the 18th-19th centuries using both corpus-linguistic-quantitative and qualitative methods. Situating itself in both historical/diachronic discourse research and corpus-assisted discourse analysis (Partington et al. 2013), it provides the first linguistic account of the historiographical register in the pivotal period of its gradual scientification and institutionalisation. By adopting an interdisciplinary perspective, this work mediates between historiographic theorising and linguistic theory and methodology

‘A Singular Cross-cultural Poetics in a Dual Discourse’ A Study of Lin Yutang’s Self-translation of the Little Critic Essays and Between Tears and Laughter

This thesis approaches Lin Yutang’s Chinese-oriented discourse from his two self-translation projects, rendering respectively his Little Critic column essays and Between Tears and Laughter. The research carried out for this thesis aims to analyse Lin’s self-translation changes, to compare the differences in motivational patterns between these two projects, and to offer possible justification for the unique character of Lin’s text decisions. Due to the heterolinguistic nature of this research project, the research is informed by the domain of Translation Studies, borrowing the broad framework from the ‘architectonics of translation analysis’ by Berman that combine a text analysis and a translator study, and also sources analytical tools from some well-established findings based on linguistics. Hence, this research hopes to enrich the research setting of self-translation in Translation Studies, in the sense that the uniqueness of Lin’s text decisions serves as an example of how self-translators’ decisions differ from allograph translators’