Sensitivity to input distributions and decision boundaries in auditory category learning.

Abstract

Previous research demonstrates the sensitivity of adults and infants to the statistical regularity of input distributions defining speech categories [D. L. Grieser and P. K. Kuhl, Dev. Psychol. 25, 577–588 (1989)] and even non-human animals exhibit such sensitivity [Kluender et al., J. Acoust. Soc. Am. 104, 3568–3580 (1998)]. Speech categories’ structure also possesses information to support the use of decision boundaries in categorization. To investigate the interaction of distribution versus decision-boundary information in auditory category learning, the current research tracked listeners learning novel non-speech categories defined by two acoustic dimensions, the center frequency and modulation frequency, via explicit training with feedback. Early in learning, listeners exhibited sensitivity to distributional regularities of categories by robustly responding to more densely sampled regions of acoustic space. However, evidence of listeners’ reliance on a decision boundary emerged once learning plateaued. The point in learning at which decision boundaries predicted categorization response was determined not only by the type of listeners’ prior experience with the sounds but also by the perceptual salience of the acoustic dimensions. [Work supported by NSF.]