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This paper presents the integration of a natural language generation system onto an In-Home Domain Dialogue System to achieve fluent, non-redundant verbal descriptions of the state of the environment. Three important contributions are brought together in this integration: an in-depth study of aggregation strategies preferred by users in the In-Home Domain, a fully operational dialogue system, and a natural language generation system capable of implementing the required aggregation strategies. The integration is validated by means of acceptance tests with human evaluators. In this paper we show how the aggregation strategies remove redundancies and provide a description that is assigned higher scores by human evaluators than prior descriptions. [ABSTRACT FROM AUTHOR]

Human-Computer interaction can be clearly leveraged by using Natural Language systems, specially in interactive environments. In this paper a system which interprets a 3D virtual world in terms of human abstractions like ˵corridor″ or ˵crossroad″ and differences between world items basing on the properties the user refers to, is presented. This interpretation is oriented to human orders understanding, making it possible for the system to be interactively guided by the user. A partial implementation of the algorithm and its results are shown, and discussion about how the system could be empowered for better Natural Language Processing is detailed. [ABSTRACT FROM AUTHOR]

This paper presents an approximation towards an evolutionary generator of alliterative text. A simple text is given along with the preferred phoneme for alliterations as input. Then the evolutionary algorithm (with the aid of a phonemic transcriber, Microsoft Word and Google) will try to produce an alternative sentence while trying to preserve the initial meaning and coherence. A bigram language model and the evaluation of the phonetic analysis are used to assess the fitness of the sentences. [ABSTRACT FROM AUTHOR]

The growing availability of GPS and localization technologies opens up new challenges regarding the use of position information for Location Based Services. As a side effect, several research questions arise, one of which we consider in this paper: "What is the meaning of place?". Here, we present two ongoing projects that we believe can contribute to the answer. The first regards the semantic enrichment of place, starting from a simple description of the place towards a concept network; the second focuses the natural language description of this network, as a final output to the user. We present these two projects, focus on their intersection and give an example of the end results. [ABSTRACT FROM AUTHOR]

Computer-generated texts are yet far from human-generated ones. Along with the limited use of vocabulary and syntactic structures they present, their lack of creativeness and abstraction is what points them as artificial. The use of metaphors and analogies is one of the creative tools used by humans that is difficult to reproduce in a computer. A human writer would not have difficulties to find conceptual relations between the domain he is writing about and his knowledge about other domains in the world, using this information in the text avoiding possible confusion. However, this task is not trivial for a computer. This paper presents an approach to the use of metaphors for referring to concepts in an automatically generated text. From a given mapping between the concepts of two domains we intend to generate metaphors for some concepts relating them with the target metaphoric domain and insert these metaphorical references in a text. We also study the ambiguity induced by metaphor and how to reduce it. [ABSTRACT FROM AUTHOR]

The present paper describes how dependency analysis can be used to automatically extract from a corpus a set of cases - and an accompanying vocabulary - which enable a template-based generator to achieve reasonable coverage over conceptual messages beyond the explicit scope of the templates defined in it. Details are provided on the actual process of partial automation that has been applied to obtain the case base, together with the various ingredients of the template-based generator, which applies case-based reasoning techniques. This module resorts to the taxonomy of concepts in WordNet to compute similarity between concepts involved in the texts. A case retrieval net is used as a memory model. The set of data to be converted into text acts as a query to the system. The process of solving a given query may involve several retrieval processes - to obtain a set of cases that together constitute a good solution for transcribing the data in the query as text messages - and a process of knowledge-intensive adaptation which resorts to a knowledge base to identify appropriate substitutions and completions for the concepts that appear in the cases, using the query as a source. We describe this case-based solution for selecting an appropriate set of templates to render a given set of data as text, we present numeric results of system performance in the domain of press articles, and we discuss its advantages and shortcomings. [ABSTRACT FROM AUTHOR]

The present paper describes a case-based reasoning solution for solving the task of selecting adequate templates for realizing messages describing actions in a given domain. This solution involves the construction of a case base from a corpus of example texts, using information from WordNet to group related verbs together. A case retrieval net is used as a memory model. A taxonomy of the concepts involved in the texts is used to compute similarity between concepts. The set of data to be converted into text acts as a query to the system. The process of solving a given query may involve several retrieval processes - to obtain a set of cases that together constitute a good solution for transcribing the data in the query as text messages - and a process of knowledge-intensive adaptation which resorts to a knowledge base to identify appropriate substitutions and completions for the concepts that appear in the cases, using the query as a source. We describe this case-based solution, and we present examples of how it solves the task of selecting an appropriate set of templates to render a given set of data as text. [ABSTRACT FROM AUTHOR]

When building natural language generation applications it is desireable to have the possibility of assembling modules that use different techniques for each one of the specific generation tasks. This paper presents an agent-based module for referring expression generation and aggregation, implemented within the framework of a generic architecture for implementing multi-agent systems: Open Agent Architecture. [ABSTRACT FROM AUTHOR]

In this paper we present a system for automatic story generation that reuses existing stories to produce a new story that matches a given user query. The plot structure is obtained by a case-based reasoning (CBR) process over a case base of tales and an ontology of explicitly declared relevant knowledge. The resulting story is generated as a sketch of a plot described in natural language by means of natural language generation (NLG) techniques. [ABSTRACT FROM AUTHOR]

In this paper we discuss the use of Case Retrieval Nets, a particular memory model for implementing case-base reasoning solutions, for implementing a heuristic lexicalisation module within a natural language generation application. We describe a text generator for fairy tales implemented using a generic architecture, and we present examples of how the Case Retrieval Net solves the Lexicalization task. [ABSTRACT FROM AUTHOR]