Phonological word forms are maintained in long-term memory and rapidly accessed during speech. However, the neural mechanisms that support the acquisition, maintenance, and recollection of word-form memories remain unclear. Starting from the hypothesis that dendrites and cell assemblies are the neural substrate for associating phoneme sequences to words, the present study investigates the dynamics of lexical access in a biologically constrained network model and compares it to the computational principles of human spoken word recognition. The model is a spiking recurrent network of dendritic neurons with realistic physiology and connectivity. The network implements unsupervised plasticity in the excitatory and inhibitory synapses, resulting in stable associations between phonemic and word representations. The activity of word assemblies indicates that, first, lexical representations are activated incrementally; second, lexical neighbors delay correct lexical access with both cohort and rhyme groups reactivated; and third, partial phonemic mismatch degrades word recognition. We also derive the model's predictions on the lexical bias effect and show that it is consistent with the hypothesis of offline feedback, providing a plausible mechanism for perceptual learning. In conclusion, we show that the dendrites could be the missing link between the perceptual space of phonemes and the mental lexicon.