This paper provides a novel algorithm for supporting automatic learning oriented to advanced human-machine interfaces. The algorithm introduces several points of innovativeness, based on complex similarity metrics involving several features of the whole learning process. A comprehensive experimental assessment and analysis of the proposed algorithm on both synthetic and real-life data sets confirms the benefits deriving from our proposal.

Automatic Learning for Supporting Advanced Human-Machine Interfaces

Cuzzocrea Alfredo;
2015

Abstract

This paper provides a novel algorithm for supporting automatic learning oriented to advanced human-machine interfaces. The algorithm introduces several points of innovativeness, based on complex similarity metrics involving several features of the whole learning process. A comprehensive experimental assessment and analysis of the proposed algorithm on both synthetic and real-life data sets confirms the benefits deriving from our proposal.
human-machine interface
artificial utterances generation
imitation learning
talking heads
facial parameters
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/20.500.11770/312760
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