Machine recognition vs human recognition of voices

While automated speaker recognition by machines can be quite good as seen in NIST Speaker Recognition Evaluations, performance can still suffer when the environmental conditions, emotions, or recording quality changes. This research examines how robust humans are compared to machine recognition for changing environments. Several data conditions including short sentences, frequency selective noise, and time-reversed speech are used to test the robustness of both humans and machine algorithms. Statistical significance tests were completed and, for most conditions, human were more robust.