title: One hundred ways to process time, frequency, rate and scale in the central auditory system: a pattern-recognition meta-analysis.
abstract: The mammalian auditory system extracts features from the acoustic environment based on the responses of spatially distributed sets of neurons in the subcortical and cortical auditory structures. The characteristic responses of these neurons (linearly approximated by their spectro-temporal receptive fields, or STRFs) suggest that auditory representations are formed, as early as in the inferior colliculi, on the basis of a time, frequency, rate (temporal modulations) and scale (spectral modulations) analysis of sound. However, how these four dimensions are integrated and processed in subsequent neural networks remains unclear. In this work, we present a new methodology to generate computational insights into the functional organization of such processes. We first propose a systematic framework to explore more than a hundred different computational strategies proposed in the literature to process the output of a generic STRF model. We then evaluate these strategies on their ability to compute perceptual distances between pairs of environmental sounds. Finally, we conduct a meta-analysis of the dataset of all these algorithms' accuracies to examine whether certain combinations of dimensions and certain ways to treat such dimensions are, on the whole, more computationally effective than others. We present an application of this methodology to a dataset of ten environmental sound categories, in which the analysis reveals that (1) models are most effective when they organize STRF data into frequency groupings-which is consistent with the known tonotopic organization of receptive fields in auditory structures -, and that (2) models that treat STRF data as time series are no more effective than models that rely only on summary statistics along time-which corroborates recent experimental evidence on texture discrimination by summary statistics.
authors.affiliation: Centre de Robotique (CAOR), École Nationale Supérieure des Mines de Paris Paris, France.
authors.forename: Edgar
authors.initials: E
authors.lastname: Hemery
authors.affiliation: Science et Technologie de la Musique et du Son, IRCAM/Centre National de la Recherche Scientifique UMR9912/UPMC Paris, France.
authors.forename: Jean-Julien
authors.initials: JJ
authors.lastname: Aucouturier
keywords: audio pattern recognition; auditory pathway; spectro-temporal receptive fields