Discourse structure and language technology

This publication is with permission of the rights owner freely accessible due to an Alliance licence and a national licence (funded by the DFG, German Research Foundation) respectively.An increasing number of researchers and practitioners in Natural Language Engineering face the prospect of having to work with entire texts, rather than individual sentences. While it is clear that text must have useful structure, its nature may be less clear, making it more difficult to exploit in applications. This survey of work on discourse structure thus provides a primer on the bases of which discourse is structured along with some of their formal properties. It then lays out the current state-of-the-art with respect to algorithms for recognizing these different structures, and how these algorithms are currently being used in Language Technology applications. After identifying resources that should prove useful in improving algorithm performance across a range of languages, we conclude by speculating on future discourse structure-enabled technology.Peer Reviewe

Critical Discourse Analysis Using Norman Fairclough Model on MediaIndonesia.com Merdeka Belajar Episode 26

    This research aims to find out how the news construction about the Merdeka Belajar policy Episode 26 released by the Ministry of Education, Culture, Research and Technology was packaged using Nourman Fairclough's critical discourse analysis. This research method uses qualitative research analysis with the scalpel of critical discourse analysis developed by Norman Fairclough. The research data used is the MediaIndonesia.com news text published on August 29 2023. The research results reveal that critical discourse analysis emphasizes discourse as a form of interaction through the use of spoken and written language as a form of social practice. Social practice in critical discourse analysis is related to events from a reality and social structure. The role of the media cannot be separated from ideological practices, meaning that the media presents news using certain constructions to attract readers' interest. MediaIndonesia.com presents emerging realities with the character of selecting titles and discourse that are appropriate to the news context. The language used in news texts is packaged lightly, briefly and easily understood by the wider public. &nbsp

Multilingual Extension of PDTB-Style Annotation: The Case of TED Multilingual Discourse Bank

We introduce TED-Multilingual Discourse Bank, a corpus of TED talks transcripts in 6 languages (English, German, Polish, EuropeanPortuguese, Russian and Turkish), where the ultimate aim is to provide a clearly described level of discourse structure and semanticsin multiple languages. The corpus is manually annotated following the goals and principles of PDTB, involving explicit and implicitdiscourse connectives, entity relations, alternative lexicalizations and no relations. In the corpus, we also aim to capture the character-istics of spoken language that exist in the transcripts and adapt the PDTB scheme according to our aims; for example, we introducehypophora. We spot other aspects of spoken discourse such as the discourse marker use of connectives to keep them distinct from theirdiscourse connective use. TED-MDB is, to the best of our knowledge, one of the few multilingual discourse treebanks and is hoped tobe a source of parallel data for contrastive linguistic analysis as well as language technology applications. We describe the corpus, theannotation procedure and provide preliminary corpus statistics.info:eu-repo/semantics/publishedVersio

A CRITICAL DISCOURSE ANALYSIS OF MOHAMAD NASIR’S SPEECH

ABSTRACT Discourse is a unit of language in which its form is longer than a sentence including the vast majority of everyday communication; in addition, it ussually employes specific kinds of language as well as infromation structures to deliver specific purposes. In order to identify the structure and purpose of a discourse, the present research employed Critical Discourse Analysis (CDA) to analyze an educational speech in May 2nd, 2016 delivered by the Indonesian Ministry of Research, Technology, and Higher Education, Mohamad Nasir in the celebration of the National Education Day of Indonesia. The result of the analysis showed how the speech was constructed in form of macrostructure, superstructure, and microstructure revealed how the social power was used by symbolic elites to invite all parties in educational field to join together in reforming educational system of Indonesia to be better than what had been conducted by previous partisans in the past. Keywords: Critical Discourse Analysis (CDA); Indonesian Ministry’s speech; educational speech; National Education Da

Teaching within a university: an in depth study of the every day use of technology

The assumptions underpinning this study are that in order to understand the real use of technology in teaching it is necessary to examine the everyday world of the university (Eisner & Peshkin, 1990, p. 99) and then to ‘tell it as it is’. The enquiry process is approached from a disciplinary context by capturing the views and actual practice of technology use in teaching of thirteen academics from different disciplinary fields within one university. A case study methodology framed the design of the study, requiring the collection of data from a variety of sources in order to describe the university which defined the study. My intention was to answer the following question: How is the use of technology shaped by the everyday teaching practice of academics within a university? The aim of the study therefore was to explore the use of technology by examining the academic’s views about how technology affected the way that they understood teaching. A feature of contemporary research into technology and teaching is an emphasis on small, context specific case studies. These often separate teaching and learning from other aspects of cultural practice, such as disciplinary and other institutional influences. In this study Bernstein’s theory of pedagogic discourse and his categories of recognition and realisation, along with the concepts of classification and framing provided a detailed coding structure as a way of analysing the resulting interview data. Analysis of practical examples of technology use in teaching revealed that academics are influenced by ideological conceptions of epistemic and social relations that are inherent within their own values and beliefs about their own roles and those of students. The coding structure revealed a variety of pedagogic practice linked to vertical (i.e complex) language use or horizontal (i.e everyday) language use. The detailed case studies of technology use by the individual academics gave rise to four different categories of teaching - knowledge and knower modes of teaching, with a vocational or non-vocational focus. This thesis contributes to professional knowledge in this field because of the use of a social theory which highlights the complex relationship between technology and pedagogic discourse and the institutional and disciplinary forces that shape the relationship

The political discourse and material practice of technology enhanced learning

Technology discloses man’s mode of dealing with Nature, the process of production by which he sustains his life, and thereby also lays bare the mode of formation of his social relations, and of the mental conceptions that flow from them (Marx, 1990: 372) My thesis is a Sociological analysis of UK policy discourse for educational technology during the last 15 years. My framework is a dialogue between the Marxist-based critical social theory of Lieras and a corpus-based Critical Discourse Analysis (CDA) of UK policy for Technology Enhanced Learning (TEL) in higher education. Embedded in TEL is a presupposition: a deterministic assumption that technology has enhanced learning. This conceals a necessary debate that reminds us it is humans that design learning, not technology. By omitting people, TEL provides a vehicle for strong hierarchical or neoliberal, agendas to make simplified claims politically, in the name of technology. My research has two main aims: firstly, I share a replicable, mixed methodological approach for linguistic analysis of the political discourse of TEL. Quantitatively, I examine patterns in my corpus to question forms of ‘use’ around technology that structure a rigid basic argument which ‘enframes’ educational technology (Heidegger, 1977: 38). In a qualitative analysis of findings, I ask to what extent policy discourse evaluates technology in one way, to support a Knowledge Based Economy (KBE) in a political economy of neoliberalism (Jessop 2004, Fairclough 2006). If technology is commodified as an external enhancement, it is expected to provide an ‘exchange value’ for learners (Marx, 1867). I therefore examine more closely what is prioritised and devalued in these texts. Secondly, I disclose a form of austerity in the discourse where technology, as an abstract force, undertakes tasks usually ascribed to humans (Lieras, 1996, Brey, 2003:2). This risks desubjectivisation, loss of power and limits people’s relationships with technology and with each other. A view of technology in political discourse as complete without people closes possibilities for broader dialectical (Fairclough, 2001, 2007) and ‘convivial’ (Illich, 1973) understandings of the intimate, material practice of engaging with technology in education. In opening the ‘black box’ of TEL via CDA I reveal talking points that are otherwise concealed. This allows me as to be reflexive and self-critical through praxis, to confront my own assumptions about what the discourse conceals and what forms of resistance might be required. In so doing, I contribute to ongoing debates about networked learning, providing a context to explore educational technology as a technology, language and learning nexus

Dialogue Act Modeling for Automatic Tagging and Recognition of Conversational Speech

We describe a statistical approach for modeling dialogue acts in conversational speech, i.e., speech-act-like units such as Statement, Question, Backchannel, Agreement, Disagreement, and Apology. Our model detects and predicts dialogue acts based on lexical, collocational, and prosodic cues, as well as on the discourse coherence of the dialogue act sequence. The dialogue model is based on treating the discourse structure of a conversation as a hidden Markov model and the individual dialogue acts as observations emanating from the model states. Constraints on the likely sequence of dialogue acts are modeled via a dialogue act n-gram. The statistical dialogue grammar is combined with word n-grams, decision trees, and neural networks modeling the idiosyncratic lexical and prosodic manifestations of each dialogue act. We develop a probabilistic integration of speech recognition with dialogue modeling, to improve both speech recognition and dialogue act classification accuracy. Models are trained and evaluated using a large hand-labeled database of 1,155 conversations from the Switchboard corpus of spontaneous human-to-human telephone speech. We achieved good dialogue act labeling accuracy (65% based on errorful, automatically recognized words and prosody, and 71% based on word transcripts, compared to a chance baseline accuracy of 35% and human accuracy of 84%) and a small reduction in word recognition error.Comment: 35 pages, 5 figures. Changes in copy editing (note title spelling changed

Linguistics and LIS: A Research Agenda

Linguistics and Library and Information Science (LIS) are both interdisciplinary fields that draws from areas such as languages, psychology, sociology, cognitive science, computer science, anthropology, education, and management. The theories and methods of linguistic research can have significant explanatory power for LIS. This article presents a research agenda for LIS that proposes the use of linguistic analysis methods, including discourse analysis, typology, and genre theory

Joint Modeling of Content and Discourse Relations in Dialogues

We present a joint modeling approach to identify salient discussion points in spoken meetings as well as to label the discourse relations between speaker turns. A variation of our model is also discussed when discourse relations are treated as latent variables. Experimental results on two popular meeting corpora show that our joint model can outperform state-of-the-art approaches for both phrase-based content selection and discourse relation prediction tasks. We also evaluate our model on predicting the consistency among team members' understanding of their group decisions. Classifiers trained with features constructed from our model achieve significant better predictive performance than the state-of-the-art.Comment: Accepted by ACL 2017. 11 page