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- W1974677719 abstract "Janko et al. [Binaural and Spatial Hearing in Real and Virtual Environments, edited by Gilkey and Anderson (Erlbaum, Hillsdale, NJ, 1996), pp. 557–570] used neural networks to describe auditory localization and found that data in quiet were insufficient to discriminate among models. To further constrain the models, localization in the presence of a spatially fixed masker is considered here. The wideband targets and maskers were filtered by head-related transfer functions, then by a gammatone filter bank. A model for binaural interaction similar to that of Lindemann [J. Acoust. Soc. Am. 80, 1608–1622 (1986)] was used to process the filter-bank outputs. The inhibited cross-correlation output of the binaural processor was sampled and used as input to a neural network (e.g., 24 correlation lags at each of 13 frequency channels for 312 input nodes). The network was trained using back propagation to estimate the target location in quiet, then tested on targets in noise at several values of signal-to-noise ratio (SNR). The network was also trained across several values of SNR. Results are compared to localization in noise by humans [Good and Gilkey, J. Acoust. Soc. Am. 99, 1108–1117 (1996)]. [Work supported by AFOSR F49620-95-1-0106 and the Ohio Board of Regents.]" @default.
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- W1974677719 date "1998-05-01" @default.
- W1974677719 modified "2023-10-18" @default.
- W1974677719 title "A model of auditory localization in noise using neural networks" @default.
- W1974677719 doi "https://doi.org/10.1121/1.421512" @default.
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