The model then revises the meaning of the words in U (t) by incorporating the alignment probabilities for the current input pair.
moreover, the overall behaviour of our model confirms that the probabilistic bootstrapping approach to word learning naturally leads to the onset of fast mapping in the course of lexical development, without hard-coding any specialized learning mechanism into the model to account for this phenomenon.