Follow-ups and interpreter-mediated discourse

The edited volume documents the proceedings of the ESF workshop "Follow-ups across discourse domains: a cross-cultural exploration of their forms and functions". It examines the forms and functions of the dialogue act of a follow-up, viz. accepting or challenging a prior communicative act, in political discourse across spoken and written dialogic genres. Specifically, it considers (1) the discourse domains of political interviews, editorials, op-eds and discussion forums, (2) their sequential organization as regards the status of initial (or 1st order) follow-up, a follow-up of a prior follow-up (2nd order follow-up), or nth-order follow-up, and (3) their discursive realization as regards degrees of indirectness and responsiveness which are conceptualized as a continuum along the lines of degrees of explicitness and degrees of responsiveness. The chapters come from the fields of linguistics, discourse analysis, socio-pragmatics, communication, political science and psychology, examining the heterogeneous field of political discourse and its manifestation in diverse discourse genres with respect to evasiveness, indirectness and redundancy in mediated political discourse, professional discourse, discourse identity and doing politics, to name but the most prominent questions

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

Inter-Coder Agreement for Computational Linguistics

This article is a survey of methods for measuring agreement among corpus annotators. It exposes the mathematics and underlying assumptions of agreement coefficients, covering Krippendorff's alpha as well as Scott's pi and Cohen's kappa; discusses the use of coefficients in several annotation tasks; and argues that weighted, alpha-like coefficients, traditionally less used than kappa-like measures in computational linguistics, may be more appropriate for many corpus annotation tasks—but that their use makes the interpretation of the value of the coefficient even harder. </jats:p

Limited Attention and Discourse Structure

This squib examines the role of limited attention in a theory of discourse structure and proposes a model of attentional state that relates current hierarchical theories of discourse structure to empirical evidence about human discourse processing capabilities. First, I present examples that are not predicted by Grosz and Sidner's stack model of attentional state. Then I consider an alternative model of attentional state, the cache model, which accounts for the examples, and which makes particular processing predictions. Finally I suggest a number of ways that future research could distinguish the predictions of the cache model and the stack model.Comment: 9 pages, uses twoside,cl,lingmacro

Centering, Anaphora Resolution, and Discourse Structure

Centering was formulated as a model of the relationship between attentional state, the form of referring expressions, and the coherence of an utterance within a discourse segment (Grosz, Joshi and Weinstein, 1986; Grosz, Joshi and Weinstein, 1995). In this chapter, I argue that the restriction of centering to operating within a discourse segment should be abandoned in order to integrate centering with a model of global discourse structure. The within-segment restriction causes three problems. The first problem is that centers are often continued over discourse segment boundaries with pronominal referring expressions whose form is identical to those that occur within a discourse segment. The second problem is that recent work has shown that listeners perceive segment boundaries at various levels of granularity. If centering models a universal processing phenomenon, it is implausible that each listener is using a different centering algorithm.The third issue is that even for utterances within a discourse segment, there are strong contrasts between utterances whose adjacent utterance within a segment is hierarchically recent and those whose adjacent utterance within a segment is linearly recent. This chapter argues that these problems can be eliminated by replacing Grosz and Sidner's stack model of attentional state with an alternate model, the cache model. I show how the cache model is easily integrated with the centering algorithm, and provide several types of data from naturally occurring discourses that support the proposed integrated model. Future work should provide additional support for these claims with an examination of a larger corpus of naturally occurring discourses.Comment: 35 pages, uses elsart12, lingmacros, named, psfi

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

Vicarious learning through capturing task‐directed discussions

The vicarious learner group has been developing a multimedia database system to promote and enhance the role of dialogue in learning. A specific interest, and the origin of the projects' collective name, is in the question of whether and how dialogue can be helpfully ‘reused’. What benefits can students gain from dialogue as observers, not just as participants? We describe our initial attempts to generate and capture educationally effective discourse exchanges amongst and between students and tutors. Problems encountered with available CMC discourse formats led to our development of a set of Task Directed Discussions (TDDs). A medium‐sized corpus of discourse exchanges was collected using the TDDs. A selection of nearly two hundred of these TDD exchanges formed the multimedia discourse database to the implemented prototype system, Dissemination. Initial results from a controlled experiment and evaluation of Dissemination are outline

From conditioning to learning communities: Implications of fifty years of research in e‐learning interaction design

This paper will consider e‐learning in terms of the underlying learning processes and interactions that are stimulated, supported or favoured by new media and the contexts or communities in which it is used. We will review and critique a selection of research and development from the past fifty years that has linked pedagogical and learning theory to the design of innovative e‐learning systems and activities, and discuss their implications. It will include approaches that are, essentially, behaviourist (Skinner and Gagné), cognitivist (Pask, Piaget and Papert), situated (Lave, Wenger and Seely‐Brown), socio‐constructivist (Vygotsky), socio‐cultural (Nardi and Engestrom) and community‐based (Wenger and Preece). Emerging from this review is the argument that effective e‐learning usually requires, or involves, high‐quality educational discourse, that leads to, at the least, improved knowledge, and at the best, conceptual development and improved understanding. To achieve this I argue that we need to adopt a more holistic approach to design that synthesizes features of the included approaches, leading to a framework that emphasizes the relationships between cognitive changes, dialogue processes and the communities, or contexts for e‐learning