Discovering acoustic structure of novel sounds.

Abstract

Natural sounds have substantial acoustic structure (predictability, nonrandomness) in their spectral and temporal compositions. Listeners are expected to exploit this structure to distinguish simultaneous sound sources; however, previous studies confounded acoustic structure and listening experience. Here, sensitivity to acoustic structure in novel sounds was measured in discrimination and identification tasks. Complementary signal-processing strategies independently varied relative acoustic entropy (the inverse of acoustic structure) across frequency or time. In one condition, instantaneous frequency of low-pass-filtered 300-ms random noise was rescaled to 5 kHz bandwidth and resynthesized. In another condition, the instantaneous frequency of a short gated 5-kHz noise was resampled up to 300 ms. In both cases, entropy relative to full bandwidth or full duration was a fraction of that in 300-ms noise sampled at 10 kHz. Discrimination of sounds improved with less relative entropy. Listeners identified a probe sound as a target sound (1%, 3.2%, or 10% relative entropy) that repeated amidst distractor sounds (1%, 10%, or 100% relative entropy) at 0 dB SNR. Performance depended on differences in relative entropy between targets and background. Lower-relative-entropy targets were better identified against higher-relative-entropy distractors than lower-relative-entropy distractors; higher-relative-entropy targets were better identified amidst lower-relative-entropy distractors. Results were consistent across signal-processing strategies.