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Computer models for masked hearing experiments with beluga whales (Delphinapterus leucas).

C Erbe1, A R King, M Yedlin

  • 1Institute of Ocean Sciences, Sidney, British Columbia, Canada.

The Journal of the Acoustical Society of America
|May 21, 1999
PubMed
Summary

Software models can predict how manmade ocean noise affects marine mammal communication. A back-propagation neural network closely simulated beluga whale hearing experiments, offering a cost-effective alternative to animal testing for environmental noise assessments.

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Area of Science:

  • Marine biology
  • Bioacoustics
  • Computational acoustics

Background:

  • Environmental assessments require understanding manmade noise impacts on marine mammal vocalizations.
  • Direct animal experiments are time-consuming, costly, and often impractical for such assessments.

Purpose of the Study:

  • To evaluate the efficacy of software models in predicting noise interference with animal vocalizations.
  • To compare model performance against empirical data from beluga whale hearing experiments.

Main Methods:

  • Utilized signal processing techniques including matched filter, spectrogram cross-correlation, and critical band cross-correlation.
  • Employed a back-propagation neural network to detect beluga vocalizations in various ocean noise conditions.
  • Compared model outputs with masked hearing experiments conducted on a beluga whale.

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Main Results:

  • The back-propagation neural network demonstrated the highest fidelity in simulating the beluga whale's masked hearing data.
  • All tested models showed capability in detecting beluga vocalizations amidst different ocean noise types.
  • The neural network approach provides a promising method for predicting noise-vocalization interference.

Conclusions:

  • Software models, particularly artificial neural networks, can reliably estimate the effects of anthropogenic noise on marine mammal communication.
  • This approach offers a feasible and efficient alternative to traditional animal testing for environmental noise impact studies.
  • Findings support the use of computational models in marine mammal conservation and acoustic management strategies.