Objective
Content creation is a fundamental activity for developing identities in modern individuals. Yet creativity is hardly addressed by computer science. This project addresses the issue of content creation from the perspective of Flow machines. Flow machines are interactive systems that learn how to generate content, text or music, in the user’s style. Thanks to controlled generation mechanisms, the user can then steer the machine to generate content that fits with their intentions. Flow interactions induce a multiplicative effect that boosts creativity and prompts the user to reflect on their own style. This vision stems from the success stories of several computer-assisted musical systems that showed how interactive dialogs with self-learning interactions provoke flow states.
To enables full control of stylistic generation, the scientific challenge is the reification of style as a flexible texture. This challenge will be addressed by pursuing three original directions in the fields of statistical learning and combinatorial optimization: 1) the formulation of Markov-based generation as a constraint problem, 2) the development of feature generation techniques for feeding machine learning algorithms and 3) the development of techniques to transform descriptors into controllers.
Two large-scale studies will be conducted with well-known creators using these Flow machines, during which the whole creation process will be recorded, stored, and analyzed, providing the first complete chronicles of professional-level artifacts. The artifacts, a music album and a novel, will be published in their respective ecosystems, and the reaction of the audience will be measured and analyzed to further assess the impact of Flow machines on creation. The technologies developed and the pilot studies will serve as pioneering experiments to turn Flow machines into a field of study and explore other domains of creation.
Fields of science (EuroSciVoc)
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
CORDIS classifies projects with EuroSciVoc, a multilingual taxonomy of fields of science, through a semi-automatic process based on NLP techniques. See: The European Science Vocabulary.
- natural sciences biological sciences ecology ecosystems
- natural sciences computer and information sciences artificial intelligence machine learning
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Programme(s)
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Multi-annual funding programmes that define the EU’s priorities for research and innovation.
Topic(s)
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Calls for proposals are divided into topics. A topic defines a specific subject or area for which applicants can submit proposals. The description of a topic comprises its specific scope and the expected impact of the funded project.
Call for proposal
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
Procedure for inviting applicants to submit project proposals, with the aim of receiving EU funding.
ERC-2011-ADG_20110209
See other projects for this call
Funding Scheme
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Funding scheme (or “Type of Action”) inside a programme with common features. It specifies: the scope of what is funded; the reimbursement rate; specific evaluation criteria to qualify for funding; and the use of simplified forms of costs like lump sums.
Host institution
75252 PARIS
France
The total costs incurred by this organisation to participate in the project, including direct and indirect costs. This amount is a subset of the overall project budget.