Discourse analysis considers how language, both spoken and written, enacts
social and cultural perspectives and identities. Assuming no prior knowledge
of linguistics, An Introduction to Discourse Analysis examines the field and
presents James Paul Gee’s unique integrated approach, which incorporates
both a theory of language-in-use and a method of research.
DESIGN DISCOURSE: COMPOSING AND REVISING PROGRAMS IN PROFESSIONAL AND TECHNICAL WRITING addresses the complexities of developing professional and technical writing programs. The essays in the collection offer reflections on efforts to bridge two cultures-what the editors characterize as the "art and science of writing"-often by addressing explicitly the tensions between them. DESIGN DISCOURSE offers insights into the high-stakes decisions made by program designers as they seek to "function at the intersection of the practical and the abstract, the human and the technical." Contribut...
A groundbreaking study of urban sprawl in Calgary, "Expansive Discourses" looks at the city’s development after the Second World War. The interactions of land developers and the local government influenced how the pattern grew: developers met market demands and optimized profits by building houses as efficiently as possible, while the city had to consider wider planning constraints and infrastructure costs.In "Expansive Discourses", Foran examines the complexity of their debates from a historical perspective, why each party acted as it did, and where each can be criticized....
To understand a speaker's turn of a conversation, one needs to segment it into intonational phrases, clean up any speech repairs that might have occurred, and identify discourse markers. In this paper, we argue that these problems must be resolved together, and that they must be resolved early in the processing stream. We put forward a statistical language model that resolves these problems, does POS tagging, and can be used as the language model of a speech recognizer.
Presentations "Multimodal discourse analysis" present on: Limitations of multimodal discourse analysis, analysis the picture, background to multimodal discourse analysis and introduce the picture. Invite you to consult.
We present a novel model to represent and assess the discourse coherence of text. Our model assumes that coherent text implicitly favors certain types of discourse relation transitions. We implement this model and apply it towards the text ordering ranking task, which aims to discern an original text from a permuted ordering of its sentences.
We present a series of experiments on automatically identifying the sense of implicit discourse relations, i.e. relations that are not marked with a discourse connective such as “but” or “because”. We work with a corpus of implicit relations present in newspaper text and report results on a test set that is representative of the naturally occurring distribution of senses. We use several linguistically informed features, including polarity tags, Levin verb classes, length of verb phrases, modality, context, and lexical features. ...
This paper describes the design and application of time-enhanced, finite state models of discourse cues to the automated segmentation of broadcast news. We describe our analysis of a broadcast news corpus, the design of a discourse cue based story segmentor that builds upon information extraction techniques, and finally its computational implementation and evaluation in the Broadcast News Navigator (BNN) to support video news browsing, retrieval, and summarization. explicit discourse cues (e.g., "the first", "the most important") to perform tasks such as summarization (Paice 1981). ...
It is claimed that a variety of facts concerning ellipsis, event reference, and interclausal coherence can be explained by two features of the linguistic form in question: (1) whether the form leaves behind an empty constituent in the syntax, and (2) whether the form is anaphoric in the semantics. It is proposed that these features interact with one of two types of discourse inference, namely Common Topic inference and Coherent Situation inference.
Conversation between two people is usually of MIXED-INITIATIVE, with CONTROL over the conversation being transferred from one person to another. We apply a set of rules for the transfer of control to 4 sets of dialogues consisting of a total of 1862 turns. The application of the control rules lets us derive domain-independent discourse structures. The derived structures indicate that initiative plays a role in the structuring of discourse.
The way in which discourse features express connections back to the previous discourse has been described in the literature in terms of adjoining at the right frontier of discourse structure. But this does not allow for discourse features that express ezpectations about what is to come in the subsequent discourse. After characterizing these expectations and their distribution in text, we show how an approach that makes use of substitution as well as adjoining on a suitably defined right frontier, can be used to both process expectations and constrain discouse processing in general. ...
An experiment in the computer generation of coherent discourse was successfully conducted to test a hypothesis about the transitive nature of syntactic dependency relations among elements of the English language.
This paper describes a novel approach towards the empirical approximation of discourse relations between different utterances in texts. Following the idea that every pair of events comes with preferences regarding the range and frequency of discourse relations connecting both parts, the paper investigates whether these preferences are manifested in the distribution of relation words (that serve to signal these relations).
Discourse references, notably coreference and bridging, play an important role in many text understanding applications, but their impact on textual entailment is yet to be systematically understood. On the basis of an in-depth analysis of entailment instances, we argue that discourse references have the potential of substantially improving textual entailment recognition, and identify a number of research directions towards this goal.
This tutorial aims to provide attendees with a clear notion of how discourse structure is relevant for language technology (LT), what is needed for exploiting discourse structure, what methods and resources are available to support its use, and what more could be done in the future. (a) Discourse chunking and parsing (b) Recognizing arguments and sense of discourse connectives (c) Recognizing and generating entitybased discourse structure (d) Dialogue parsing 3.
Temporal–contrastive discourse connectives (although, while, since, etc.) signal various types of relations between clauses such as temporal, contrast, concession and cause. They are often ambiguous and therefore difﬁcult to translate from one language to another.
This paper introduces a new algorithm to parse discourse within the framework of Rhetorical Structure Theory (RST). Our method is based on recent advances in the ﬁeld of statistical machine learning (multivariate capabilities of Support Vector Machines) and a rich feature space. RST offers a formal framework for hierarchical text organization with strong applications in discourse analysis and text generation.
Articles in the Penn TreeBank were identiﬁed as being reviews, summaries, letters to the editor, news reportage, corrections, wit and short verse, or quarterly proﬁt reports. All but the latter three were then characterised in terms of features manually annotated in the Penn Discourse TreeBank — discourse connectives and their senses. Summaries turned out to display very different discourse features than the other three genres. Letters also appeared to have some different features.
Underspeciﬁcation-based algorithms for processing partially disambiguated discourse structure must cope with extremely high numbers of readings. Based on previous work on dominance graphs and weighted tree grammars, we provide the ﬁrst possibility for computing an underspeciﬁed discourse description and a best discourse representation efﬁciently enough to process even the longest discourses in the RST Discourse Treebank.