Sperm Whale Signal Analysis: Comparison Using the AutoRegressive Model and the Daubechies 15 Wavelets Transform

This article presents the results using a parametric approach and a Wavelet Transform in analysing signals emitting from the sperm whale. The extraction of intrinsic characteristics of these unique signals emitted by marine mammals is still at present a difficult exercise for various reasons: firstly, it concerns nonstationary signals, and secondly, these signals are obstructed by interfering background noise. In this article, we compare the advantages and disadvantages of both methods: AutoRegressive models and Wavelet Transform. These approaches serve as an alternative to the commonly used estimators which are based on the Fourier Transform for which the hypotheses necessary for its application are in certain cases, not sufficiently proven. These modern approaches provide effective results particularly for the periodic tracking of the signal's characteristics and notably when the signal-to-noise ratio negatively effects signal tracking. Our objectives are twofold. Our first goal is to identify the animal through its acoustic signature. This includes recognition of the marine mammal species and ultimately of the individual animal (within the species). The second is much more ambitious and directly involves the intervention of cetologists to study the sounds emitted by marine mammals in an effort to characterize their behaviour. We are working on an approach based on the recordings of marine mammal signals and the findings from this data result from the Wavelet Transform. This article will explore the reasons for using this approach. In addition, thanks to the use of new processors, these algorithms once heavy in calculation time can be integrated in a realtime system. Keywords—autoregressive model, Daubechies Wavelet, Fourier Transform, marine mammals, signal processing, spectrogram, sperm whale, Wavelet Transform.

[1]  Ingrid Daubechies,et al.  Ten Lectures on Wavelets , 1992 .

[2]  David A. Helweg,et al.  Acoustic identification of female Steller sea lions , 2000 .

[3]  Ulrich Parlitz,et al.  Methods of chaos physics and their application to acoustics , 1988 .

[4]  Robert J. Urick,et al.  Principles of underwater sound , 1975 .

[5]  R. W. Floyd,et al.  Measurement of echolocation signals of the Atlantic bottlenose dolphin, Tursiops truncatus Montagu, in open waters. , 1974, The Journal of the Acoustical Society of America.

[6]  Geoffrey E. Hinton,et al.  Learning representations by back-propagation errors, nature , 1986 .

[7]  H. Akaike.  A new look at the statistical model identification , 1974 .

[8]  Isao Tokuda,et al.  Nonlinear analysis of irregular animal vocalizations. , 2002, The Journal of the Acoustical Society of America.

[9]  THE CLICK-SOUNDS OF NARWHALS , 1995 .

[10]  K. S. Norris,et al.  a Theory for the Function of the Spermaceti Organ of the Sperm Whale (physeter Catodon L) , 1972 .

[12]  G. G. Stokes.  "J." , 1890, The New Yale Book of Quotations.

[13]  William A. Watkins,et al.  Sperm whale codas , 1977 .

[14]  D. Moretti,et al.  New algorithms for open ocean marine mammal monitoring , 2000, OCEANS 2000 MTS/IEEE Conference and Exhibition. Conference Proceedings (Cat. No.00CH37158).

[15]  Jacques Max,et al.  Méthodes et techniques de traitement du signal et applications aux mesures physiques : principes et appareillages de traitement en temps réel , 1977 .

[16]  Rodney F. W. Coates,et al.  Underwater Acoustic Systems , 1990 .

[17]  Geoffrey E. Hinton,et al.  Learning representations of back-propagation errors , 1986 .

[18]  J. Goold,et al.  Time and frequency domain characteristics of sperm whale clicks. , 1995, The Journal of the Acoustical Society of America.

[19]  John Goold,et al.  Sound velocity measurements in spermaceti oil under the combined influences of temperature and pressure , 1996 .

[20]  J. Max.  Méthodes et techniques de traitement du signal et application aux mesures physiques. Tome 2 , 1981 .

[21]  Michael B. Porter,et al.  Automated model-based localization of marine mammals near Hawaii , 2001, MTS/IEEE Oceans 2001. An Ocean Odyssey. Conference Proceedings (IEEE Cat. No.01CH37295).

[22]  P ? ? ? ? ? ? ? % ? ? ? ? , 1991 .

[23]  P. Laguna,et al.  Signal Processing , 2002, Yearbook of Medical Informatics.

[24]  L. Miller,et al.  Sperm whale clicks: directionality and source level revisited. , 2000, The Journal of the Acoustical Society of America.

[25]  Geoffrey E. Hinton,et al.  Learning representations by back-propagating errors , 1986, Nature.

[26]  Christopher W. Clark,et al.  A method for filtering bioacoustic transients by spectrogram image convolution , 1993, Proceedings of OCEANS '93.