A generalized power-law detection algorithm for humpback whale vocalizations

Abstract

Conventional detection of humpback vocalizations is often based on frequency summation of band-limited spectrograms under the assumption that energy (square of the Fourier amplitude) is the appropriate metric. Power-law detectors allow for a higher power of the Fourier amplitude, appropriate when the signal occupies a limited but unknown subset of these frequencies. Shipping noise is non-stationary and colored and problematic for many marine mammal detection algorithms. Modifications to the standard power-law form are introduced to minimize the effects of this noise. These same modifications also allow for a fixed detection threshold, applicable to broadly varying ocean acoustic environments. The detection algorithm is general enough to detect all types of humpback vocalizations. Tests presented in this paper show this algorithm matches human detection performance with an acceptably small probability of false alarms (P(FA) < 6%) for even the noisiest environments. The detector outperforms energy detection techniques, providing a probability of detection P(D) = 95% for P(FA) < 5% for three acoustic deployments, compared to P(FA) > 40% for two energy-based techniques. The generalized power-law detector also can be used for basic parameter estimation and can be adapted for other types of transient sounds.

Validating the reliability of passive acoustic localisation: a novel method for encountering rare and remote Antarctic blue whales

“…The success of this study, coupled with the decreasing cost and size of computing hardware and ongoing improvements of automated detection and classification software (e.g. Baumgartner & Mussoline 2011, Helble et al 2012 further affirms that real-time passive acoustic localisation can greatly improve our capacity to study rare baleen whales. Finally, Peel et al (2014) provide a freely available simulation framework that could be used to assess the potential improvement in encounter rate offered by this type of passive acoustic tracking.…”

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

“…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.…”

Obtaining Cue Rate Estimates for Some Mysticete Species using Existing Data

“…Previous efforts resulted in ambiguous animal locations, and localization efforts were abandoned. However, new techniques using methods partially described in Helble et al, 2012 have allowed for unambiguous animal locations, even during periods of multiple calling animals (see INITIAL RESULTS). The PMRF dataset also provides opportunities to calculate animal densities from other mysticetes, including fin and sei (Balaenoptera borealis) whales.…”

“…In the near term, the SCORE range datasets can be used to track humpback whales, providing cue rates for transiting humpback whales off the coast of California. Because significant work has already been conducted on developing a viable humpback detection algorithm (Helble et al, 2012), and calculating the site specific probability of detection at certain locations off the coast of California (Helble et al, 2013a), obtaining a cue rate for the region will immediately yield humpback whale density estimates for transiting humpback whales in the southern California region (Helble et al, 2013c).…”