A comparison of novices and experts in the identification of sonar signals

This research contrasted trained sonar operators with novices in their abilities to categorize sonar signals as being of biological or man-made origin. Although the sonar operators performed significantly better than the naive subjects, the performance of the naive subjects (d' = 1.39) was closer to that of the sonar operators (d' = 1.81) than to chance. Additionally, there were qualitative similarities in the two groups' performances. In order to understand this, a new group of people listened to a subset of 76 of the sounds, and chose verbal descriptors from a detailed list of 146 words such as "pht". "chuck-chuck", "rainfall", etc. to describe each sound. Analyses of the descriptor choices demonstrated that biological sound sources were identifiable as such simply because they sounded like animal noises. Man-made signals were identified as more percussive, a result confirmed by an acoustical analysis of the signals. Two scales were developed for the signals, indicating how "animal like" and how percussive they were, respectively. Either of the two scales could predict with about 75% accuracy the category of the signals, a level of accuracy equal to that of the novices, and not bested by neither a CART model nor a neural net model. A simple acoustical analysis of the percussiveness of the waveforms could predict people's judgments, but not predict the objective classifications of the signals. (C) 2004 Elsevier B.V. All rights reserved.