Accent Interpretation, Anaphora Resolution and Implicature Derivation

Abstract not available

Presenting Arguments as Fictive Dialogue

Presentation of an argument can take many different forms ranging from a monologue to advanced graphics and diagrams. This paper investigates the presentation of one or more arguments in the form of a fictive dialogue. This technique was already employed by Plato, who used fictive conversations between Socrates and his contemporaries to put his arguments forward. Ever since, there have been influential authors – including Desiderius Erasmus, Sir Thomas More and Mark Twain – that have used dialogue in this way. In this paper, we define the notion of a fictive dialogue, motivate it is as a topic for investigation, and present a qualitative and quantitative study of five fictive dialogues by well-known authors. We conclude by indicating how our preliminary and ongoing investigations may inform the development of systems that automatically generate argumentative fictive dialogue

A Flexible pragmatics-driven language generator for animated agents

This paper describes the NECA MNLG; a fully implemented Multimodal Natural Language Generation module. The MNLG is deployed as part of the NECA system which generates dialogues between animated agents. The generation module supports the seamless integration of full grammar rules, templates and canned text. The generator takes input which allows for the specification of syntactic, semantic and pragmatic constraints on the output

Salience and pointing in multimodal reference

Pointing combined with verbal referring is one of the most paradigmatic human multimodal behaviours. The aim of this paper is foundational: to uncover the central notions that are required for a computational model of human-generated multimodal referring acts. The paper draws on existing work on the generation of referring expressions and shows that in order to extend that work with pointing, the notion of salience needs to play a pivotal role. The paper investigates the role of salience in the generation of referring expressions and introduces a distinction between two opposing approaches: salience-first and salience-last accounts. The paper then argues that these differ not only in computational efficiency, as has been pointed out previously, but also lead to incompatible empirical predictions. The second half of the paper shows how a salience first account nicely meshes with a range of existing empirical findings on multimodal reference. A novel account of the circumstances under which speakers choose to point is proposed that directly links salience with pointing. Finally, a multidimensional model of salience is proposed to flesh this model out

Dialogue with computers: dialogue games in action

With the advent of digital personal assistants for mobile devices, systems that are marketed as engaging in (spoken) dialogue have reached a wider public than ever before. For a student of dialogue, this raises the question to what extent such systems are genuine dialogue partners. In order to address this question, this study proposes to use the concept of a dialogue game as an analytical tool. Thus, we reframe the question as asking for the dialogue games that such systems play. Our analysis, as applied to a number of landmark systems and illustrated with dialogue extracts, leads to a fine-grained classification of such systems. Drawing on this analysis, we propose that the uptake of future generations of more powerful dialogue systems will depend on whether they are self-validating. A self-validating dialogue system can not only talk and do things, but also discuss the why of what it says and does, and learn from such discussions

A Formal Semantics for Editing and Generating Plurals

We present a formal semantics for an object-oriented formalism which allows for the representation of plural objects (such as 'Three N', Most of the N', 'Some N', . . .). the semantics is given in terms of a mapping to a variant of Discourse Representation Theory. It is motivated by its suitability for natural language generation and interactives editing of the representations

Modality Choice for Generation of Referring Acts: Pointing versus Describing

The main aim of this paper is to challenge two commonly held assumptions regarding modality selection in the generation of referring acts: the assumption that non-verbal means of referring are secondary to verbal ones, and the assumption that there is a single strategy that speakers follow for generating referring acts. Our evidence is drawn from a corpus of task-oriented dialogues that was obtained through an observational study. We propose two alternative strategies for modality selection based on correlation data from the observational study. Speakers that follow the first strategy simply abstain from pointing. Speakers that follow the other strategy make the decision whether to point dependent on whether the intended referent is in focus and/or important. This decision precedes the selection of verbal means (i.e., words) for referring

Generating expository dialogue from monologue: Motivation, corpus and preliminary rules

Generating expository dialogue from monologue is a task that poses an interesting and rewarding challenge for Natural Language Processing. This short paper has three aims: firstly, to motivate the importance of this task, both in terms of the benefits of expository dialogue as a way to present information and in terms of potential applications; secondly, to introduce a parallel corpus of monologues and dialogues which enables a data-driven approach to this challenge; and, finally, to describe work-in-progress on semi-automatic construction of Monologueto-Dialogue (M2D) generation rules

Collecting Reliable Human Judgements on Machine-Generated Language: The Case of the QG-STEC Data

Question generation (QG) is the problem of automatically generating questions from inputs such as declarative sentences. The Shared Evaluation Task Challenge (QG-STEC) Task B that took place in 2010 evaluated several state-of-the-art QG systems. However, analysis of the evaluation results was affected by low inter-rater reliability. We adapted Nonaka & Takeuchi’s knowledge creation cycle to the task of improving the evaluation annotation guidelines with a preliminary test showing clearly improved inter-rater reliability

Question generation in the CODA project

In the ongoing CODA project, we are developing a system for automatically converting monologue into dialogue. The dialogue is generated in a two-step approach. Firstly, snippets of input monologue are mapped to dialogue act sequences. Secondly, these sequences are verbalized. The conversion relies partly on analysing input monologue in terms of its discourse relations. This short paper briefly describes the approach to the first step in CODA. This approach involves the use of a parallel corpus of monologues and dialogues to learn mappings from monologue to dialogue acts. Here, we focus on dialogue acts that involve question asking