Guillaume Aimetti

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This paper reports the ongoing research of a thesis project investigating a computational model of early language acquisition. The model discovers word-like units from cross-modal input data and builds continuously evolving internal representations within a cog-nitive model of memory. Current cognitive theories suggest that young infants employ general(More)
A multilingual speech corpus used for modeling language acquisition called CAREGIVER has been designed and recorded within the framework of the EU funded Acquisition of Communication and Recognition Skills (ACORNS) project. The paper describes the motivation behind the corpus and its design by relying on current knowledge regarding infant language(More)
In this paper we compare three different implementations of language learning to investigate the issue of speaker-dependent initial representations and subsequent generalization. These implementations are used in a comprehensive model of language acquisition under development in the FP6 FET project ACORNS. All algorithms are embedded in a cognitively and(More)
This paper introduces a computational model that automatically segments acoustic speech data and builds internal representations of keyword classes from cross-modal (acoustic and pseudo-visual) input. Acoustic segmentation is achieved using a novel dynamic time warping technique and the focus of this paper is on recent investigations conducted to enhance(More)
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