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Distributed dynamic REpresentations for diAlogue Management

Project description

Computational modelling for a deeper understanding of human language use

Modelling the ability to communicate using language via computational methods is an exciting open problem. To tackle this challenge, the EU-funded DREAM project will create new computational models of dialogue agents that learn how to engage in conversation directly from data involving language use. The project combines ideas from linguistics with new developments in machine learning related to artificial neural network systems. This will enable dialogue agents to learn the representations that they manipulate directly from experience. The dialogue agents will learn from human conversations that have a task-oriented goal. The project will advance the development of complex conversational agents and improve scientific understanding of human language use.

Objective

Our ability to communicate using language in conversation is considered the hallmark of human intelligence. Yet, while holding a dialogue is effortless for most of us, modelling this basic human skill by computational means has proven extremely difficult. In DREAM, I address this challenge by establishing a new computational model of a dialogue agent that can learn to take part in conversation directly from data about language use. DREAM stands at the crossroads of the symbolic and the sub-symbolic traditions regarding the nature of human cognitive processing and, by extension, its computational modelling. My model is grounded in linguistic theories of dialogue, rooted in the symbolic tradition, but exploits recent advances in computational learning that allow the agent to learn the representations that it manipulates, which are distributed and sub-symbolic, directly from experience. This is an original approach that constitutes a paradigm shift in dialogue modelling --- from predefined symbolic representations to automatic representation learning --- that will break new scientific ground in Computational Linguistics, Linguistics, and Artificial Intelligence. The DREAM agent will be implemented as an artificial neural network system and trained with task-oriented conversations where the participants have a well-defined end goal. The agent will be able to integrate linguistic and perceptual information and will be endowed with the capability to dynamically track both speaker commitments and partner-specific conventions, leading to more human-like and effective communication. Besides providing a breakthrough in our capacity to build sophisticated conversational agents, DREAM will have substantial impact on our scientific understanding of human language use, thanks to its emphasis on theory-driven hypotheses and model analysis.

Host institution

UNIVERSITEIT VAN AMSTERDAM
Net EU contribution
€ 2 000 000,00
Address
SPUI 21
1012WX Amsterdam
Netherlands

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Region
West-Nederland Noord-Holland Groot-Amsterdam
Activity type
Higher or Secondary Education Establishments
Links
Total cost
€ 2 000 000,00

Beneficiaries (1)