Using salience and hypothesis evaluation to learn object names in real time

Abstract

This paper presents a computational model of word learning that has roots in experimental literature and learns in real time with high precision from a small amount of data. In addition to incorporating external cues a la Yu & Ballard 2007, we give the learner the ability to test specific highly probable semantic hypotheses against new data. Performance is… (More)

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