In this paper we investigate a computational model of word learning that is cognitively plausible. The model is partly trained on incorrect form-referent pairings, modelling the input to a word-learning child that may contain such mismatches due to inattention to a joint communicative scene. We introduce a procedure of active learning, based on attested cognitive processes. We then show how this procedure can help overcome the unreliability of the input by detecting and correcting the mismatches by reliance on previously built up experience.