L0—the first five years of an automated language acquisition project
Artificial Intelligence Review - Special issue: grounding representations
On image auto-annotation with latent space models
MULTIMEDIA '03 Proceedings of the eleventh ACM international conference on Multimedia
Grounded spoken language acquisition: experiments in word learning
IEEE Transactions on Multimedia
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It is proposed an approach for the automatic description of scenes using a LSA–like technique. The described scenes are composed by a set of elements that can be geometric forms or iconic representation of objects. Every icon is characterized by a set of attributes like shape, colour and position. Each scene is related to a set of sentences describing their content. The proposed approach builds a data driven vector semantic space where the scenes and the sentences are mapped. A new scene can be mapped in this created space accordingly to a suitable metric. Preliminary experimental results show the effectiveness of the procedure.