Perceptual learning of novel sounds
To recognize a sound, it is necessary to extract its auditory features, although we do not yet know what these auditory features are. Here, we show that there is not a simple set of features, but rather that new features can be learnt to recognize previously unheard sounds. The behavioral measure [Agus, Thorpe, & Pressnitzer, Neuron, 2010] was based on the detection of repetitions in 1s-long noises, some of which re-occurred throughout an experimental block. Repetitions in the re-occurring noises were detected more frequently, showing learning of otherwise meaningless sounds. The learning was unsupervised, resilient to interference, and rapid, and generalizable to similar noises. Multiple noises were remembered for several weeks and listeners learnt unrepeated noises. A second set of experiments showed faster selective responses to voices than for acoustically comparable sounds. These results collectively point towards an active mechanism that learns auditory features affecting everyday recognition of everyday sounds.
Trevor Agus is a researcher studying hearing in the Laboratoire Psychologie de la Perception and at the Departement d’études cognitives at the Ecole normale supérieure. He is particularly interested in how the auditory system processes complex sounds, typical of those encountered in everyday life. He believes that by better understanding the features used to recognize and segregate sound objects, it may be possible to better manage the effects of hearing-impairment.
Trevor obtained a BA in mathematics at the University of Cambridge, and an MSc in Music Technology at the University of York. His PhD in Psychology was obtained at the University of Strathclyde in conjunction with the Institute of Hearing Research Scottish Section, based in Glasgow, before starting his post-doctoral research with Daniel Pressnitzer in Paris.