Controlling redundancy in referring expressions

Krahmer et al.’s (2003) graph-based framework provides an elegant and flexible approach to the generation of referring expressions. In this paper, we present the first reported study that systematically investigates how to tune the parameters of the graph-based framework on the basis of a corpus of human-generated descriptions. We focus in particular on replicating the redundant nature of human referring expressions, whereby properties not strictly necessary for identifying a referent are nonetheless included in descriptions. We show how statistics derived from the corpus data can be integrated to boost the framework’s performance over a non-stochastic baseline

Collaborating on Referring Expressions

This paper presents a computational model of how conversational participants collaborate in order to make a referring action successful. The model is based on the view of language as goal-directed behavior. We propose that the content of a referring expression can be accounted for by the planning paradigm. Not only does this approach allow the processes of building referring expressions and identifying their referents to be captured by plan construction and plan inference, it also allows us to account for how participants clarify a referring expression by using meta-actions that reason about and manipulate the plan derivation that corresponds to the referring expression. To account for how clarification goals arise and how inferred clarification plans affect the agent, we propose that the agents are in a certain state of mind, and that this state includes an intention to achieve the goal of referring and a plan that the agents are currently considering. It is this mental state that sanctions the adoption of goals and the acceptance of inferred plans, and so acts as a link between understanding and generation.Comment: 32 pages, 2 figures, to appear in Computation Linguistics 21-

Production of Referring Expressions for an Unknown Audience : a Computational Model of Communal Common Ground

The research reported in this article is based on the Ph.D. project of Dr. RK, which was funded by the Scottish Informatics and Computer Science Alliance (SICSA). KvD acknowledges support from the EPSRC under the RefNet grant (EP/J019615/1).Peer reviewedPublisher PD

From Linearity to Circulation. How TV Flow Is Changing in Networked Media Space

This article discusses the evolution of the concept of flow from the producer-controlled phase to the user-controlled phase, thus proposing the concept of circulation as a new framework for understanding the new TV ecosystem. The multiplication of screens (from the traditional TV set to handheld mobile devices) has made TV content accessible anytime and anywhere and, furthermore, has provided an interactive space where the digital life of content is managed by the audiences on social media. Such multiplication of screens has created forms of TV consumption that lead to the deconstruction and subsequent reformulation of the concepts of space, time and medium. This article examines this ongoing process, beginning with observations of audience consumption practices that are analysed using Osservatorio Social TV 2015, an Italian research project

Survey of the State of the Art in Natural Language Generation: Core tasks, applications and evaluation

This paper surveys the current state of the art in Natural Language Generation (NLG), defined as the task of generating text or speech from non-linguistic input. A survey of NLG is timely in view of the changes that the field has undergone over the past decade or so, especially in relation to new (usually data-driven) methods, as well as new applications of NLG technology. This survey therefore aims to (a) give an up-to-date synthesis of research on the core tasks in NLG and the architectures adopted in which such tasks are organised; (b) highlight a number of relatively recent research topics that have arisen partly as a result of growing synergies between NLG and other areas of artificial intelligence; (c) draw attention to the challenges in NLG evaluation, relating them to similar challenges faced in other areas of Natural Language Processing, with an emphasis on different evaluation methods and the relationships between them.Comment: Published in Journal of AI Research (JAIR), volume 61, pp 75-170. 118 pages, 8 figures, 1 tabl

The “return” of performance art from a glocal perspective

Various authors have characterized the contemporary world through the notion of "structural hybridization" (Pieterse 2001; Canclini 2001, among others). This notion refers to the mixing of different times and spaces that gives rise to "spatiotemporal" hybrid configurations. One of the factors of this process is usually translated by the term "hybrid cycles" (Stross 1999), through which a new cycle recovers historical and social characteristics of previous cycles, sometimes distant in time. Through this theoretical framework, which combines concepts such as hybridity, cyclicality, mimesis, reflexivity and performativity, this paper intends to problematize issues such as the so-called "social turn" (Bishop 2006)or "return to the real" (Foster 2001) in art or, more generally, the "performative turn" (Alexander 2006), with the aim of analyzing the cyclical dynamic of performance (social) art (an art that relies on notions of participation and even performative intervention in a public space) from a global perspective – from Portugal to the world and vice versa