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368
Automatic generation of textual summaries from neonatal intensive care data
- In Proccedings of the 11th Conference on Artificial Intelligence in Medicine (AIME ’07). LNCS
, 2007
"... Intensive care is becoming increasingly complex. If mistakes are to be avoided, there is a need for the large amount of clinical data to be presented effectively to the medical staff. Although the most common approach is to present the data graphically, it has been shown that textual summarisation c ..."
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Cited by 74 (32 self)
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Intensive care is becoming increasingly complex. If mistakes are to be avoided, there is a need for the large amount of clinical data to be presented effectively to the medical staff. Although the most common approach is to present the data graphically, it has been shown that textual summarisation can lead to improved decision making. As the first step in the BabyTalk project, a prototype is being developed which will generate a textual summary of 45 minutes of continuous physiological signals and discrete events (e.g.: equipment settings and drug administration). Its architecture brings together techniques from the different areas of signal analysis, medical reasoning, and natural language generation. Although the current system is still being improved, it is powerful enough to generate meaningful texts containing the most relevant information. This prototype will be extended to summarize several hours of data and to include clinical interpretation. 1
Microplanning with Communicative Intentions: The SPUD System
- Computational Intelligence
, 2001
"... The process of microplanning encompasses a range of problems in Natural Language Generation (NLG), such as referring expression generation, lexical choice, and aggregation, problems in which a generator must bridge underlying domain-specific representations and general linguistic representations. In ..."
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Cited by 71 (17 self)
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The process of microplanning encompasses a range of problems in Natural Language Generation (NLG), such as referring expression generation, lexical choice, and aggregation, problems in which a generator must bridge underlying domain-specific representations and general linguistic representations. In this paper, we describe a uniform approach to microplanning based on declarative representations of a generator's communicative intent. These representations describe the RE- SULTS of NLG: communicative intent associates the concrete linguistic structure planned by the generator with inferences that show how the meaning of that structure communicates needed information about some application domain in the current discourse context. Our approach, implemented in the SPUD (sentence planning using description) microplanner, uses the lexicalized treeadjoining grammar formalism (LTAG) to connect structure to meaning and uses modal logic programming to connect meaning to context. At the same time, communicative intent representations provide a RESOURCE for the PROCESS of NLG. Using representations of communicative intent, a generator can augment the syntax, semantics and pragmatics of an incomplete sentence simultaneously, and can assess its progress on the various problems of microplanning incrementally. The declarative formulation of communicative intent translates into a well-defined methodology for designing grammatical and conceptual resources which the generator can use to achieve desired microplanning behavior in a specified domain. Contents 1 Motivation 3 2
Text Generation in a Dynamic Hypertext Environment
- In Proceedings of the 19th Australasian Computer Science Conference
, 1996
"... This paper describes PEBA-II, a working natural language generation system which interactively describes animals in a taxonomic knowledge base via the production of World Wide Web pages. Our aim is to construct a natural language document generation system with real practical applicability: to this ..."
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Cited by 63 (13 self)
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This paper describes PEBA-II, a working natural language generation system which interactively describes animals in a taxonomic knowledge base via the production of World Wide Web pages. Our aim is to construct a natural language document generation system with real practical applicability: to this end, the system reconstructs and combines a number of existing ideas in the literature in a novel way, and proposes a solution to the problem of breadth of coverage that is based on a pragmatic approach to knowledge representation and linguistic realisation. The system embodies the following features: ffl a reconstruction of some of the core ideas in schema--based text generation [McKeown 1985], applied to the generation of hypertext documents; ffl the principled use of a phrasal lexicon to ease surface generation, in concert with a knowledge base whose elements may correspond to pre--compiled collections of atomic units; ffl a user model and discourse model that permit interesting varia...
Generating Minimal Definite Descriptions
- In Proc. ACL-02
, 2002
"... The incremental algorithm introduced in (Dale and Reiter, 1995) for producing distinguishing descriptions does not always generate a minimal description. In this paper, I show that when generalised to sets of individuals and disjunctive properties, this approach might generate unnecessarily l ..."
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Cited by 53 (0 self)
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The incremental algorithm introduced in (Dale and Reiter, 1995) for producing distinguishing descriptions does not always generate a minimal description. In this paper, I show that when generalised to sets of individuals and disjunctive properties, this approach might generate unnecessarily long and ambiguous and/or epistemically redundant descriptions. I then present an alternative, constraint-based algorithm and show that it builds on existing related algorithms in that (i) it produces minimal descriptions for sets of individuals using positive, negative and disjunctive properties, (ii) it straightforwardly generalises to n-ary relations and (iii) it is integrated with surface realisation.
Learning Content Selection Rules for Generating Object Descriptions in Dialogue
- Journal of Artificial Intelligence Research
, 2005
"... A fundamental requirement of any task-oriented dialogue system is the ability to generate object descriptions that refer to objects in the task domain. The subproblem of content selection for object descriptions in task-oriented dialogue has been the focus of much previous work and a large number of ..."
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Cited by 50 (1 self)
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A fundamental requirement of any task-oriented dialogue system is the ability to generate object descriptions that refer to objects in the task domain. The subproblem of content selection for object descriptions in task-oriented dialogue has been the focus of much previous work and a large number of models have been proposed. In this paper, we use the annotated coconut corpus of task-oriented design dialogues to develop feature sets based on Dale & Reiter’s incremental model, Brennan & Clark’s conceptual pact model, and Jordan’s intentional influences model, and use these feature sets in a machine learning experiment to automatically learn a model of content selection for object descriptions. Since Dale & Reiter’s model requires a representation of discourse structure, the corpus annotations are used to derive a representation based on Grosz & Sidner’s theory of the intentional structure of discourse, as well as two very simple representations of discourse structure based purely on recency. We then apply the rule-induction program ripper to train and test the content selection component of an object description generator on a set of 393 object descriptions from the corpus. To our knowledge, this is the first reported
RRL: A Rich Representation Language for the Description of Agent Behaviour in NECA
- IN PROCEEDINGS OF THE WORKSHOP EMBODIED
, 2002
"... In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is a formal framework for representing the information that is exchanged at the interfaces between the various N ..."
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Cited by 45 (19 self)
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In this paper, we describe the Rich Representation Language (RRL) which is used in the NECA system. The NECA system generates interactions between two or more animated characters. The RRL is a formal framework for representing the information that is exchanged at the interfaces between the various NECA system modules.
Learning Visually-Grounded Words and Syntax for a Scene Description Task
"... A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedure in which visual scenes are paired with natural language descriptions. Learning algorithms acquire probabilistic struct ..."
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Cited by 41 (17 self)
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A spoken language generation system has been developed that learns to describe objects in computer-generated visual scenes. The system is trained by a `show-and-tell' procedure in which visual scenes are paired with natural language descriptions. Learning algorithms acquire probabilistic structures which encode the visual semantics of phrase structure, word classes, and individual words. Using these structures, a planning algorithm integrates syntactic, semantic, and contextual constraints to generate natural and unambiguous descriptions of objects in novel scenes.
Computational Generation of Referring Expressions: A Survey
, 2009
"... This article offers a survey of computational research on referring expressions generation (REG). It introduces the REG problem and describes early work in this area, discussing what basic assumptions lie behind it, and showing how its remit has considerably widened in recent years. We discuss compu ..."
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Cited by 39 (12 self)
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This article offers a survey of computational research on referring expressions generation (REG). It introduces the REG problem and describes early work in this area, discussing what basic assumptions lie behind it, and showing how its remit has considerably widened in recent years. We discuss computational frameworks underlying REG, and demonstrate a recent trend that seeks to link up REG algorithms with well-established Knowledge Representation traditions. Considerable attention is given to recent efforts at evaluating REG algorithms and the lessons that they allow us to learn. The article concludes with a discussion of what we see as the way forward in REG, focussing on references in larger and more realistic settings.
Generating referring expressions that involve gradable properties
- Computational Linguistics
, 2006
"... This paper examines the role of gradable properties in referring expressions, from a perspective of natural language generation. Firstly, we propose a simple seman-tic analysis of vague descriptions (i.e., referring expressions that contain grad-able adjectives) that reflects the context-dependent m ..."
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Cited by 37 (10 self)
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This paper examines the role of gradable properties in referring expressions, from a perspective of natural language generation. Firstly, we propose a simple seman-tic analysis of vague descriptions (i.e., referring expressions that contain grad-able adjectives) that reflects the context-dependent meaning of the adjectives in them. Secondly, we show how this type of analysis can inform algorithms for the generation of vague descriptions from numerical data. Thirdly, we ask when such descriptions should be used. The paper concludes with a discussion of salience and pointing, which are analysed as if they were gradable adjectives.
Using natural language generation in automatic route description
- Journal of Research and Practice in Information Technology
, 2005
"... In this paper we tackle the problem of generating natural route descriptions on the basis of input obtained from a commercially available way-finding system. Our framework and architecture incorporates the use of general principles drawn from the domain of natural language generation. Through exampl ..."
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Cited by 35 (1 self)
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In this paper we tackle the problem of generating natural route descriptions on the basis of input obtained from a commercially available way-finding system. Our framework and architecture incorporates the use of general principles drawn from the domain of natural language generation. Through examples we demonstrate that it is possible to bridge the gap between underlying data representations and natural sounding linguistic descriptions. The work presented contributes both to the area of natural language generation and to the improvement of way-finding system interfaces.