Understanding auditory distance estimation by humpback whales: a computational approach.

Abstract:

:Ranging, the ability to judge the distance to a sound source, depends on the presence of predictable patterns of attenuation. We measured long-range sound propagation in coastal waters to assess whether humpback whales might use frequency degradation cues to range singing whales. Two types of neural networks, a multi-layer and a single-layer perceptron, were trained to classify recorded sounds by distance traveled based on their frequency content. The multi-layer network successfully classified received sounds, demonstrating that the distorting effects of underwater propagation on frequency content provide sufficient cues to estimate source distance. Normalizing received sounds with respect to ambient noise levels increased the accuracy of distance estimates by single-layer perceptrons, indicating that familiarity with background noise can potentially improve a listening whale's ability to range. To assess whether frequency patterns predictive of source distance were likely to be perceived by whales, recordings were pre-processed using a computational model of the humpback whale's peripheral auditory system. Although signals processed with this model contained less information than the original recordings, neural networks trained with these physiologically based representations estimated source distance more accurately, suggesting that listening whales should be able to range singers using distance-dependent changes in frequency content.

journal_name

Behav Processes

journal_title

Behavioural processes

authors

Mercado E 3rd,Green SR,Schneider JN

doi

10.1016/j.beproc.2007.10.007

subject

Has Abstract

pub_date

2008-02-01 00:00:00

pages

231-42

issue

2

eissn

0376-6357

issn

1872-8308

pii

S0376-6357(07)00306-3

journal_volume

77

pub_type

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