Recent studies have shown that, instead, of a dichotomy between parallel and serial search strategies, in many instances we see a combination of both search strategies utilized. Consequently, computational models and theoretical accounts of visual search processing have evolved from traditional serial-parallel descriptions to a continuum from 'efficient' to 'inefficient' search. One of the findings, consistent with this blurring of the serial-parallel distinction, is that concurrent spoken linguistic input influences the efficiency of visual search. In our first experiment we replicate those findings using a between-subjects design. Next, we utilize a localist attractor network to simulate the results from the first experiment, and then employ the network to make quantitative predictions about the influence of subtle timing differences of real-time language processing on visual search. These model predictions are then tested and confirmed in our second experiment. The results provide further evidence toward understanding linguistically mediated influences on real-time visual search processing and support an interactive processing account of visual search and language comprehension.