Flexible Natural Language Generation in Multiple Contexts (original) (raw)
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Natural language generation in dialog systems
Proceedings of the first international conference on Human language technology research - HLT '01, 2001
Recent advances in Automatic Speech Recognition technology have put the goal of naturally sounding dialog systems within reach. However, the improved speech recognition has brought to light a new problem: as dialog systems understand more of what the user tells them, they need to be more sophisticated at responding to the user. The issue of system response to users has been extensively studied by the natural language generation community, though rarely in the context of dialog systems. We show how research in generation can be adapted to dialog systems, and how the high cost of hand-crafting knowledge-based generation systems can be overcome by employing machine learning techniques.
Natural Language Generation in Dialogue Systems for Customer Care
Proceedings of the Seventh Italian Conference on Computational Linguistics CLiC-it 2020
English. In this paper we discuss the role of natural language generation (NLG) in modern dialogue systems (DSs). In particular, we will study the role that a linguistically sound NLG architecture can have in a DS. Using real examples from a new corpus of dialogue in customer-care domain, we will study how the non-linguistic contextual data can be exploited by using NLG.
2009
At the start of the project, research in the field of dialogue systems had not addressed issues of natural language generation that are an integral part of the communication cycle. Natural language generation (NLG) research had achieved practical solutions to specific tasks as independent research modules, but they were difficult tointerrelate and integrate with other applications. The first goal of the project was the development of a flexible and modular software solution, capable of working with ontologies and the emotional content of messages. This solution should provide a set of reusable software components capable of generating texts suitable for different tasks in different domains. The second goal of the project was to study the application of NLG in spoken dialogue systems in a domotic environment.
DEXTOR: Reduced Effort Authoring for Template-Based Natural Language Generation
Seventh Artificial Intelligence and …, 2011
A growing issue in the development of realistic and entertaining interactive games is the need for mechanisms that support ongoing natural language conversation between human players and artificial non-player characters. Unfortunately, many methods for automating and implementing natural language generation (NLG) induce a significant burden on the author, do not scale well, or require specialized linguistic knowledge. We formalize the notion of typed-templates, an extension of standard structures employed in template-based NLG. We further provide novel algorithms that, when applied to typedtemplates, ameliorate the above issues by affording computational support for authoring and increased variation in utterance and scenario generation. We demonstrate the efficacy of typed-templates and the algorithms through a user study.
Automatic Dialogue Generator Creates User Defined Applications
We report on the development of an Automatic Dialogue Generator (ADG), a software engine with associated library files, that simplifies the generation of new applications requiring a speech interface. A key feature of the ADG is that, given any task description specified in tables, the ADG can automatically generate a finite-state dialogue for that task, in a uniform and consistent fashion. The ADG generates a connected graph structure that provides the general dialogue flow between dialogue states, as well as all the dialogue and action components within each state.
Making grammar-based generation easier to deploy in dialogue systems
Proceedings of the 9th SIGdial Workshop on Discourse and Dialogue - SIGdial '08, 2008
We present a development pipeline and associated algorithms designed to make grammarbased generation easier to deploy in implemented dialogue systems. Our approach realizes a practical trade-off between the capabilities of a system's generation component and the authoring and maintenance burdens imposed on the generation content author for a deployed system. To evaluate our approach, we performed a human rating study with system builders who work on a common largescale spoken dialogue system. Our results demonstrate the viability of our approach and illustrate authoring/performance trade-offs between hand-authored text, our grammar-based approach, and a competing shallow statistical NLG technique.
2014
At the start of the project, research in the field of dialogue systems had not addressed issues of natural language generation that are an integral part of the communication cycle. Natural language generation (NLG) research had achieved practical solutions to specific tasks as independent research modules, but they were difficult to interrelate and integrate with other applications. The first goal of the project was the development of a flexible and modular software solution, capable of working with ontologies and the emotional content of messages. This solution should provide a set of reusable software components capable of generating texts suitable for different tasks in different domains. The second goal of the project was to study the application of NLG in spoken dialogue systems in a domotic environment.
A reference architecture for natural language generation systems
Natural Language …, 2006
We present the rags (Reference Architecture for Generation Systems) framework: a specification of an abstract Natural Language Generation (NLG) system architecture to support sharing, re-use, comparison and evaluation of NLG technologies. We argue that the evidence from a survey of actual NLG systems calls for a different emphasis in a reference proposal from that seen in similar initiatives in information extraction and multimedia interfaces. We introduce the framework itself, in particular the two-level data model that allows us to support the complex data requirements of NLG systems in a flexible and coherent fashion, and describe our efforts to validate the framework through a range of implementations.
GENERIC ARCHITECTURE FOR NATURAL LANGUAGE GENERATION IN SPOKEN HUMAN-COMPUTER DIALOGUE
2000
The human-computer dialogue field is nowadays a rather developed technology and research branch in its own right, but consensus hat not been reached yet with respect to several issues. Out of these, several aspects related to answer generation in spoken natural language are addressed in this paper. First, a modular architecture integrated into a distributed, agent-based dialogue framework and in
The GEMINI platform: semi-automatic generation of dialogue applications
2004
The EC funded research project GEMINI (Generic Environment for Multilingual Interactive Natural Interfaces) has two main objectives: On the one hand the development and implementation of a platform able to produce user-friendly interactive multilingual and multi-modal dialogue interfaces to databases with a minimum of human effort and on the other hand the demonstration of the platform's efficiency through the development of two different applications using this platform. The platform consists of different assistants that help the user to semi-automatically generate dialogue applications. Its open and modular architecture simplifies the adaptability of generated applications to different use cases.