Voice tracking and spoken word recognition in the presence of other voices

We study the human hearing process by modeling the hair cell as a thresholded Hopf bifurcator and compare our calculations with experimental results involving human subjects in two different multi-source listening tasks of voice tracking and spoken-word recognition. In the model, we observed noise suppression by destructive interference between noise sources which weakens the effective noise strength acting on the hair cell. Different success rate characteristics were observed for the two tasks. Hair cell performance at low threshold levels agree well with results from voice-tracking experiments while those of word-recognition experiments are consistent with a linear model of the hearing process. The ability of humans to track a target voice is robust against cross-talk interference unlike word-recognition performance which deteriorates quickly with the number of uncorrelated noise sources in the environment which is a response behavior that is associated with linear systems.