While [11, 7,<cite> 4]</cite> focused on analyzing speech representations learnt by speech-image neural models from a phonological and semantic point of view, the present work focuses on lexical acquisition and the way speech utterances are segmented into lexical units and processed by a computational model of visually grounded speech. We analyze a key component of the neural model -the attention mechanism -and we observe its behaviour and draw parallels between artificial neural attention and human attention.