Efficient artifacts filter by density-based clustering in long term 3D whale passive acoustic monitoring with five hydrophones fixed under an Autonomous Surface Vehicle

International audiencePassive underwater acoustics allows for the monitoring of the echolocation clicks of cetaceans. Static hydrophone arrays monitor from a fixed location, however, they cannot track animals over long distances. More flexibility can be achieved by mounting hydrophones on a mobile structure. In this paper, we present the design of a small non-uniform array of five hydrophones mounted directly under the Autonomous Surface Vehicle (ASV) Sphyrna (also called an Autonomous Laboratory Vehicle) built by SeaProven in France. This configuration is made challenging by the 40cm aperture of the hydrophone array, extending only two meters below the surface and above the thermocline, thus presenting various artifacts. The array, fixed under the keel of the drone, is numerically stabilized in yaw and roll using the drone's Motion Processing Unit (MPU). To increase the accuracy of the 3D tracking computed from a four hour recording of a Sperm Whale diving several kilometers away, we propose an efficient joint filtering of the clicks in the Time Delay of Arrival (TDoA) space. We show how the DBSCAN algorithm efficiently removes any outlier detection among the thousands of transients, and yields to coherent high definition 3D tracks

High-frequency Near-field Physeter macrocephalus Monitoring by Stereo-Autoencoder and 3D Model of Sonar Organ

International audiencePassive acoustics allow us to study large animals and obtain information that could not be gathered through other methods. In this paper we study a set of near-field audiovisual recordings of a sperm whale pod, acquired with a ultra high-frequency and small aperture antenna. We propose a novel kind of autoencoder, a Stereo-Autoencoder, and show how it allows to build acoustic manifolds in order to increase our knowledge regarding the characterization of their vocalizations, and possible acoustic individual signature

Etude de sonar bio-inspiré basée sur la modélisation d'une chaîne complète d’émission-propagation-réception - Validation sur le cachalot.

The sperm whale, Physeter macrocephalus, possesses the largest biosonar in nature. Made ofmultiple oil sacs, the sperm whale sonar is tailored to function from the sea surface downto a depth of 2 kilometers, emitting clicks as loud as 236 dB, and is multipurpose, as itproduces clicks for either echolocation or socializing. However, the liquid wax that composesits sonar, made the sperm whales the target of whaling until 1986, when the remainingpopulation was far too small to remain commercially viable, especially with the arrival ofsimilar products from the petrochemical industry. The sperm whale population still facessome human threats, with the ingestion of plastic and collision with boats continuing to takea toll on their numbers. Studying sperm whales thus will have outcomes in multiple fields,in conservation, ethology, as well as in bioacoustics. Understanding the mechanism thatgoverns the sperm whale sonar will help to study these other fields, as it is a key element inthe sperm whale life. Aiming for this goal, this thesis analyzes three databases with distinctcharacteristics, obtaining the trajectory of sperm whale dives. Clicks were also linked withthe sperm whale that emitted them over multiple years of recording of the same population.An efficient End-to-End deep learning classifier was trained to classify biosonar waveforms.A simulation of wave propagation through the sperm whale head was also developed tobetter understand the complex mechanism of this sonar. Finally, a coupling method wasdeveloped to improve the parameters of the simulation using the recorded clicks from theaforementioned databases.Le cachalot, Physeter macrocephalus, possède le plus grand biosonar de la nature. Composéde plusieurs poches d’huile, le sonar du cachalot est conçu pour fonctionner de la surface de lamer jusqu’à une profondeur de 2 kilomètres, émettant des clics pouvant aller jusqu’à 236 dB,et est polyvalent, car il produit des clics pour l’écholocation ou la socialisation. Cependant,la cire liquide qui compose le sonar a fait des cachalots la cible de la chasse jusqu’en 1986,lorsque la population restante était beaucoup trop petite pour rester commercialement viable,en particulier avec l’arrivée de produits similaires développés par l’industrie pétrochimique.La population de cachalots est toujours confrontée à certaines menaces humaines, commel’ingestion de plastique et la collision avec des bateaux qui continuent de faire des ravages surleur nombres. L’étude des cachalots donne ainsi des résultats dans de multiples domaines,en conservation, en éthologie, ainsi qu’en bioacoustique. Comprendre le mécanisme qui régitle sonar du cachalot aidera à étudier ces autres domaines, car il s’agit d’un élément clé de lavie du cachalot. Dans ce but, cette thèse analyse trois bases de données aux caractéristiquesdistinctes, obtenant la trajectoire des plongées de cachalots. Les clics enregistrés ont étéégalement reliés au cachalot qui les avait émis, et ce sur plusieurs années d’enregistrementfait sur la même population. Un modèle original End-to-End par Deep Learning est construitpour classer efficacement les formes d’onde de biosonars. Une simulation de propagation desondes à travers la tête du cachalot a également été développée pour mieux comprendre lemécanisme complexe de ce sonar. Enfin, une méthode de couplage a été développée pouraméliorer les paramètres de la simulation en utilisant les clics enregistrés des bases de donnéesprécédemment citées. Un résumé de la thèse en français est présent au début du manuscrit

End to end raw audio deep learning of transients, application to bioacoustics

International audienceIn this paper, we propose a raw audio deep learning of clicks, building specific convolution filters in high dimension to elaborate complex TF representation. The CNN has 12 layers for several thousands of audio bins in inputs, and a dozen of output classes. We test this model on the international DCLDE challenge of 3 To of clicks (http://sabiod.org/DCLDE). This challenge was open in 2018, but no team answered before. At our knowledge, our model is the first raw audio click classifier with nearly 70% accurray on a dozen of classes. We discuss on the class confusions of the model and possible enhancement using data augmentation and regulation

END TO END RAW AUDIO DEEP LEARNING OF TRANSIENTS, APPLICATION TO BIOACOUSTICS

International audienc

DOCC10: Open access dataset of marine mammal transient studies and end-to-end CNN classification

International audienceClassification of transients is a difficult task. In bioacoustics, almost all studies are still done with human labeling. In passive acoustic monitoring (PAM), the data to label are made up from months of continuous recordings with multiple recording stations and the time required to label everything with human labeling is longer than the next recording session will take to produce new data, even with multiple experts. To help lay a foundation for the emergence of automatic labeling of marine mammal transients, we built a dataset using weak labels from a 3TB dataset of marine mammal transients of DCLDE 2018. The DCLDE dataset was made for a click classification challenge. The new dataset has strong labels and opened a new challenge, DOCC10, whose baseline is also described in this paper. The accuracy of 71% of the baseline is already good enough to curate the large dataset, leaving only some regions of interest still to be expertised. But this is far from perfect, and there remains space for future improvement, or challenging alternative techniques. A smaller version of DOCC10 named DOCC7 is also presented

Passive acoustic monitoring of sperm whales and anthropogenic noise using stereophonic recordings in the Mediterranean Sea, North West Pelagos Sanctuary

International audienceA total of 147 days spread over 4 years were recorded by a stereophonic sonobuoy set up in the Mediterranean sea, near the coast of Toulon, south of France. These recordings were analyzed in the scope of studying sperm whales (Physeter macrocephalus) and the impact anthropic noises may have on this species. With the use of a novel approach, which combines the use of a stereophonic antenna with a neural network, 226 sperm whales’ passages have been automatically detected in an effective range of 32 km. This dataset was then used to analyze the sperm whales’ abundance, the background noise, the influence of the background noise on the acoustic presence, and the animals’ size. The results show that sperm whales are present all year round in groups of 1–9 individuals, especially during the daytime. The estimated density is 1.69 whales/1000 km2. Animals were also less frequent during periods with an increased background noise due to ferries. The animal size distribution revealed the recorded sperm whales were distributed in length from about 7 to 15.5 m, and lonely whales are larger, while groups of two are composed of juvenile and mid-sized animals

Wave Propagation in the Biosonar Organ of sperm whales using a Finite Difference Time Domain method

International audienceThe bio-sonar of sperm whales presents many specific characteristics, such as its size, its loudness or its vocalization abilities. Furthermore it fulfills several roles in their foraging and social behaviour. However our knowledge about its operation remains limited to the main acoustic path that the emitted pulse may take. We still ignore the precise mechanisms that shape the wave and on which parts the sperm whale is able to act. In this paper, we describe a technique to simulate sperm whale click generation from a physical perspective. Such an approach aims at unveiling the processes involved in their vocal production, as a stepping stone towards a better understanding of their interaction with peers and the environment

Wave Propagation in the Biosonar Organ of sperm whales using a Finite Difference Time Domain method

International audienceThe bio-sonar of sperm whales presents many specific characteristics, such as its size, its loudness or its vocalization abilities. Furthermore it fulfills several roles in their foraging and social behaviour. However our knowledge about its operation remains limited to the main acoustic path that the emitted pulse may take. We still ignore the precise mechanisms that shape the wave and on which parts the sperm whale is able to act. In this paper, we describe a technique to simulate sperm whale click generation from a physical perspective. Such an approach aims at unveiling the processes involved in their vocal production, as a stepping stone towards a better understanding of their interaction with peers and the environment

Tag Thunder : plateforme de démonstration et d’expérimentation

International audienc