(a) Histogram of the overall sensitivity (N = 602) in the discrimination of orchestra sample libraries (OSL) and live orchestra recordings (LOR) in a single-choice paradigm. The dashed line represents the mean discrimination performance, whereas the value of 0 indicates discrimination at chance level. (b) Distribution of response bias with a mean close to 0. Negative values indicate answering response in favor of the OSL; the positive values indicate answering response in favor of the LOR. (c) Discrimination performance for groups of low sound-discrimination expertise (non-musicians, amateur musicians, musicologists, and music teachers) and high sound-discrimination expertise (orchestra musicians, audio engineers, conductors, composers, and arrangers). (d) Correct response rates (hits and correct rejections) for the total sample (72.5%), the subgroups of low vs. high sound discrimination expertise (68.6% vs. 80.0%), and Turing's criterion of 70% for correctly identifying the sound sources to prove AI. Only the group with low sound-discrimination expertise was “cheated” more easily by the samples in that they could not identify correctly the sound source above a rate of 70%.

https://doi.org/10.1371/journal.pone.0161911.g001