Detection of sperm whale clicks based on the Teager–Kaiser energy operator

Kandia, Varvara; Stylianou, Yannis

doi:10.1016/j.apacoust.2006.05.007

Cited by 100 publications

(72 citation statements)

References 21 publications

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“…This approach worked for spotted seatrout and silver perch that produced loud choruses well above the background noise of snapping shrimp (genera Alpheus and Synalpheus) but not for oyster toadfish, black drum, and red drum that had quieter calls and choruses. SPL analysis might be a way to detect presence or absence of fish calls but will not work as the sole feature in signal detection of specific fish species.Recent advances in automatic speech recognition have enabled the automatic analysis of bioacoustic signals originating from birds (Trifa et al 2008, Potamitis et al 2014, de Oliveira et al 2015, Ganchev et al 2015, amphibians (Acevedo et al 2009), terrestrial mammals (Parsons 2001, Dylla et al 2013, Zeppelzauer et al 2015, and marine mammals (Kandia & Stylianou 2006, Helble et al 2012, Pace et al 2012, Baumann-Pickering et al 2013. However, there are not many studies where signal detectors have been created to detect fish acoustic signals, especially successful ones that can identify fish calling amidst a noisy background.…”

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confidence: 99%

Long-term acoustic monitoring of fish calling provides baseline estimates of reproductive timelines in the May River estuary, southeastern USA

Monczak¹,

Berry²,

Kehrer³

et al. 2017

Mar. Ecol. Prog. Ser.

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Long-term acoustic recorders (black instrument in figure) can be used to estimate spawning timelines and rhythms by detecting fish calls associated with courtship. Design by Tim Devine, USCB Graphics ManagerMar Ecol Prog Ser 581: [1][2][3][4][5][6][7][8][9][10][11][12][13][14][15][16][17][18][19] 2017 2015). In the family Sciaenidae, sound-producing fishes include Atlantic croaker Micropogonias undulatus, silver perch Bairdiella chrysoura, black drum Pogonias cromis, spotted seatrout Cynoscion nebulosus, weakfish C. regalis, red drum Sciaenops ocellatus, spot Leiostomus xanthurus, and southern kingfish Menticirrhus americanus (Luczkovich et al. 1999, Sprague 2000, Ramcharitar et al. 2006, Gannon & Taylor 2007, Lowerre-Barbieri et al. 2008, Walters et al. 2009, Tellechea et al. 2011, Montie et al. 2015. Sound production in these fishes typically involves rapid movement of the sonic muscle surrounding the swim bladder. The resulting calls are species-specific due to anatomical differences in swim bladder and sonic muscle morphology as well as neural programming; therefore, call types can be used for species identification (Winn 1964, Ramcharitar et al. 2006.Sound production in fish species has been associated mainly with courtship behavior and reproduction (e.g. Saucier & Baltz 1993, Mann & Lobel 1995, Luczkovich et al. 2008, Walters et al. 2009, Mann et al. 2010, Montie et al. 2016, 2017. Studies have recorded underwater sounds during spawning seasons and have shown that patterns of peak calling coincide with patterns of reproductive senescence (i.e. gonadosomatic indices, sperm motility, and plasma androgen levels; Connaughton & Taylor 1995). Other wild studies have simultaneously collected acoustic recordings and plankton tows, and these data have shown that fish calling and spawning are tightly associated (Mok & Gilmore 1983, Saucier & Baltz 1993, Luczkovich et al. 1999, Aalbers & Drawbridge 2008, Lowerre-Barbieri et al. 2008. For example, the timing and amount of calling in wild weakfish were positively correlated with the timing and numbers of sciaenid eggs collected (Luczkovich et al. 1999). Similar findings have been observed in captive studies (Guest & Lasswell 1978, Connaughton & Taylor 1996, Lowerre-Barbieri et al. 2008, Montie et al. 2016, 2017. In weakfish held in laboratory tanks, courtship behavior, male calling, and spawning were correlated (Connaughton & Taylor 1996). In a quantitative study with captive red drum, findings revealed that spawning was more productive when the amount of calling increased; more eggs were collected when calls were longer in duration and contained more pulses (Montie et al. 2016). In a similar study with captive spotted seatrout, spawning was more likely to occur when male fish called more frequently; a positive relationship was found between sound pressure levels in tanks and the number of eggs collected (Montie et al. 2017). These findings indicate that acoustic metrics can accurately predict spawning potential for some soniferous fishes and that deployment of lon...

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confidence: 99%

Long-term acoustic monitoring of fish calling provides baseline estimates of reproductive timelines in the May River estuary, southeastern USA

Monczak¹,

Berry²,

Kehrer³

et al. 2017

Mar. Ecol. Prog. Ser.

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“…Therefore, we use the Teager-Kaiser (TK) energy operator Kandia & Stylianou (2006) on the discrete data:…”

Section: Teager-kaiser-mallat Filteringmentioning

confidence: 99%

“…where w(n) is a random gaussian process Kandia & Stylianou (2006). The output is dominated by the clicks energy.…”

Section: Teager-kaiser-mallat Filteringmentioning

confidence: 99%

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Highly Defined Whale Group Tracking by Passive Acoustic Stochastic Matched Filter

Benard¹,

Glotin²,

Giraudet³

2011

Advances in Sound Localization

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In this paper, we compare two low cost time-domain tracking algorithms based on passive acoustics. The problem consists in tracking an unknown number of sperm whales (Physeter catodon). Clicks are recorded on two datasets of 20 and 25 minutes on an open-ocean widely-spaced bottom-mounted hydrophone array. The output of the method is the track(s) of the Marine Mammal(s) (MM) in 3D space and time. Firstly, we briefly review studies of the Stochastic Matched Filter (SMF) detector and its performances with a reflected click cancellation, the Teager-Kaiser-Mallat (TKM) filtering, the source separation methods and the main characteristics of MM signals. Then, we propose a real-time algorithm for MM transient call localization. We also recall the Cramér-Rao Lower Bound (CRLB) Kay (1993) and the confidence ellipses theory to predict the reachable accuracy and compare it to the tracking results. In Section 3 we show and compare results of track estimates with results from specialized teams and compare SMF versus TKM localization. Then, the system is evaluated with the confidence ellipses on the trajectories. Finally, we discuss on the possible dynamic behavior of the whale that these localizations offer, like hunting and foraging strategies. This paper deals with the 3D tracking of MM using a widely-spaced bottom-mounted hydrophone array in deep water. It focuses on sperm whale clicks. There were previous algorithms developed in the state of the art Giraudet & Glotin (

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“…In general, signal samples are squared and heuristics or distributional metrics are used to determine the beginning and ending energy. As described later, we use a technique based upon the Teager energy operator which is similar to that proposed by Kandia and Stylianou (2006). Once the click is identified, typical features include the peak frequency, 3 dB bandwidth, inter-click intervals, etc.…”

Section: 21: Featuresmentioning

confidence: 99%

Marine Mammal Acoustic Monitoring and Habitat Investigation, Southern California Offshore Region

Hildebrand¹

2009

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Public reporting burden for this collection of information is estimated to average 1 hour per response, including the time for reviewing instruction, searching existing data sources, gathering and maintaining the data needed, and completing and reviewing the collection of information. Send comments regarding this burden estimate or any other aspect of this collection of information, including suggestions for reducing this burden, to Washington headquarters Services SPONSORING / MONITORING AGENCY REPORT NUMBER NPS-OC-09-00611. SUPPLEMENTARY NOTES The views expressed in this technical report are those of the authors and do not reflect the official policy or position of the Department of Defense or the U.S. Government. 12a. DISTRIBUTION / AVAILABILITY STATEMENTApproved for public release; distribution is unlimited. 12b. DISTRIBUTION CODE ABSTRACT (maximum 200 words)This report summarizes work conducted in FY2007-FY2008 to conduct marine mammal monitoring and habitat investigations in the southern California offshore region. The report describes marine mammal monitoring results during quarterly cruises, and models how physical and biological oceanographic conditions affect marine mammal habitat. Additionally, progress with constructing automatic detection and classification algorithms for acoustic monitoring of marine mammals is summarized, as is work on finite element modeling of acoustic propagation within the bodies of beaked whales and related marine mammals.Some highlights:[1] Data collected (July 2004 support the hypothesis that distributions of foraging large whales are linked to cold surface temperatures. However, winter distributions of migrating large whales don't appear to be related to habitat variables analyzed herein, and may be harder to predict based on oceanographic data.[2] A species classifier which decides whether short groups of clicks are produced by one or more individuals from three particular species is presented. The system uses the Teager energy operator and cepstral analysis.[3] Anatomical investigations and computer finite element modeling with marine mammal bodies were conducted, which resulted in two methodological advancements and the addition of more beaked whale species to the Digital Library of Anatomy. NUMBER OF PAGES 69 SUBJECT TERMS

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Detection of sperm whale clicks based on the Teager–Kaiser energy operator

Cited by 100 publications

References 21 publications

Long-term acoustic monitoring of fish calling provides baseline estimates of reproductive timelines in the May River estuary, southeastern USA

Long-term acoustic monitoring of fish calling provides baseline estimates of reproductive timelines in the May River estuary, southeastern USA

Highly Defined Whale Group Tracking by Passive Acoustic Stochastic Matched Filter

Marine Mammal Acoustic Monitoring and Habitat Investigation, Southern California Offshore Region

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