About: Deep neural network models of sound localization reveal how perception is adapted to real-world environments

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About: Deep neural network models of sound localization reveal how perception is adapted to real-world environments Goto Sponge NotDistinct Permalink

An Entity of Type : schema:ScholarlyArticle, within Data Space : covidontheweb.inria.fr associated with source document(s)

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type	Academic Article research paper schema:ScholarlyArticle
isDefinedBy	Covid-on-the-Web dataset
title	Deep neural network models of sound localization reveal how perception is adapted to real-world environments
Creator	Francl, Andrew Mcdermott, Josh
source	BioRxiv
abstract	Mammals localize sounds using information from their two ears. Localization in real-world conditions is challenging, as echoes provide erroneous information, and noises mask parts of target sounds. To better understand real-world localization we equipped a deep neural network with human ears and trained it to localize sounds in a virtual environment. The resulting model localized accurately in realistic conditions with noise and reverberation, outperforming alternative systems that lacked human ears. In simulated experiments, the network exhibited many features of human spatial hearing: sensitivity to monaural spectral cues and interaural time and level differences, integration across frequency, and biases for sound onsets. But when trained in unnatural environments without either reverberation, noise, or natural sounds, these performance characteristics deviated from those of humans. The results show how biological hearing is adapted to the challenges of real-world environments and illustrate how artificial neural networks can extend traditional ideal observer models to real-world domains.
has issue date	2020-07-22(xsd:dateTime)
bibo:doi	10.1101/2020.07.21.214486
has license	biorxiv
sha1sum (hex)	6034523a70336e6a7b26d801d39ec92256535910
schema:url	https://doi.org/10.1101/2020.07.21.214486
resource representing a document's title	Deep neural network models of sound localization reveal how perception is adapted to real-world environments
schema:publication	bioRxiv
resource representing a document's body	covid:6034523a70336e6a7b26d801d39ec92256535910#body_text
is schema:about of	named entity 'cues' named entity 'time' named entity 'trained' named entity 'adapted' named entity 'PARTS' »more»

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