Cochlear implant patients exhibit a wide range of performance on speech recognition tasks. One potential explanation for such variability is the existence of psychophysically observed phenomena that might indicate the presence of anomalous percepts associated with certain electrical stimuli, which in turn could limit the transmission of important auditory cues. Exhaustive psychophysical testing to detect all such psychophysical anomalies is time prohibitive; however, the search for anomalous channels could be expedited with prior information identifying channels potentially containing an anomaly. This study proposes a method of analyzing confusion matrices from speech token recognition tasks with the intent of identifying impaired channels. Results using both normal-hearing subjects tested with impaired acoustic models and cochlear implant subjects suggest that the proposed methods are providing information about the probability of impairment on each channel. © 2007 IEEE.