Recognition of marine mammal vocalizations in seismic environment
In partnership with Sercel, the thesis concerns the implementation of algorithms for recognizing the sounds emitted by mysticetes (baleen whales). These sounds can be studiedusing passive acoustic monitoring systems. Sercel, through its seismic activities related to oïl exploration, has its own soft...
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Other Authors: | , , , , , , , , , |
Format: | Doctoral or Postdoctoral Thesis |
Language: | French |
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HAL CCSD
2018
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Online Access: | https://theses.hal.science/tel-02090551 https://theses.hal.science/tel-02090551/document https://theses.hal.science/tel-02090551/file/2018IMTA0080_Guilment-Thomas.pdf |
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ftimtatlantique:oai:HAL:tel-02090551v1 |
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record_format |
openpolar |
institution |
Open Polar |
collection |
Archives ouvertes Hal IMT Atlantique |
op_collection_id |
ftimtatlantique |
language |
French |
topic |
Classification Marine mammal Seismic environment Sparse representation Machine learning Reconnaissance Mammifères marins Sismique Représentations parcimonieuses Apprentissage automatique [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing |
spellingShingle |
Classification Marine mammal Seismic environment Sparse representation Machine learning Reconnaissance Mammifères marins Sismique Représentations parcimonieuses Apprentissage automatique [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing Guilment, Thomas Recognition of marine mammal vocalizations in seismic environment |
topic_facet |
Classification Marine mammal Seismic environment Sparse representation Machine learning Reconnaissance Mammifères marins Sismique Représentations parcimonieuses Apprentissage automatique [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing |
description |
In partnership with Sercel, the thesis concerns the implementation of algorithms for recognizing the sounds emitted by mysticetes (baleen whales). These sounds can be studiedusing passive acoustic monitoring systems. Sercel, through its seismic activities related to oïl exploration, has its own software to detect and locate underwater sound energy sources. The thesis work therefore consists in adding a recognition module to identify if the detected andlocalized energy corresponds to a possible mysticete. Since seismic shooting campaigns areexpensive, the method used must be able to reduce the probability of false alarms, as recognitioncan invalidate detection. The proposed method is based on dictionary learning. It is dynamic, modular, depends on few parameters and is robust to false alarms. An experiment on five types of vocalizations is presented. We obtain an average recall of 92.1% while rejecting 97.3% of the noises (persistent and transient). In addition, a confidence coefficient is associated with each recognition and allows semi-supervised incremental learning to be achieved. Finally, we propose a method capable of managing detection and recognition together. This "multiclassdetector" best respects the constraints of false alarm management and allows several types of vocalizations to be identified at the same time. This method is well adapted to the industrial context for which it is dedicated. It also opens up very promising prospects in the bioacoustic context. En partenariat avec l’entreprise Sercel, la thèse concerne la mise en œuvre d’algorithmes de reconnaissance des sons émis par les mysticètes (baleines à fanons). Cessons peuvent être étudiés grâce aux systèmes de surveillance par acoustique passive. L’entreprise Sercel, par ses activités sismiques liées à la prospection pétrolière, a son propre logiciel pour détecter et localiser les sources d’énergie sonores sous-marines. Le travail de la thèse consiste dès lors à ajouter un module de reconnaissance pour identifier si l'énergie détectée et ... |
author2 |
Lab-STICC_IMTA_CID_TOMS Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT) Département Signal et Communications (IMT Atlantique - SC) IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT) Ecole nationale supérieure Mines-Télécom Atlantique Dominique Pastor |
format |
Doctoral or Postdoctoral Thesis |
author |
Guilment, Thomas |
author_facet |
Guilment, Thomas |
author_sort |
Guilment, Thomas |
title |
Recognition of marine mammal vocalizations in seismic environment |
title_short |
Recognition of marine mammal vocalizations in seismic environment |
title_full |
Recognition of marine mammal vocalizations in seismic environment |
title_fullStr |
Recognition of marine mammal vocalizations in seismic environment |
title_full_unstemmed |
Recognition of marine mammal vocalizations in seismic environment |
title_sort |
recognition of marine mammal vocalizations in seismic environment |
publisher |
HAL CCSD |
publishDate |
2018 |
url |
https://theses.hal.science/tel-02090551 https://theses.hal.science/tel-02090551/document https://theses.hal.science/tel-02090551/file/2018IMTA0080_Guilment-Thomas.pdf |
genre |
baleen whales |
genre_facet |
baleen whales |
op_source |
https://theses.hal.science/tel-02090551 Traitement du signal et de l'image [eess.SP]. Ecole nationale supérieure Mines-Télécom Atlantique, 2018. Français. ⟨NNT : 2018IMTA0080⟩ |
op_relation |
NNT: 2018IMTA0080 tel-02090551 https://theses.hal.science/tel-02090551 https://theses.hal.science/tel-02090551/document https://theses.hal.science/tel-02090551/file/2018IMTA0080_Guilment-Thomas.pdf |
op_rights |
info:eu-repo/semantics/OpenAccess |
_version_ |
1790598330444677120 |
spelling |
ftimtatlantique:oai:HAL:tel-02090551v1 2024-02-11T10:02:24+01:00 Recognition of marine mammal vocalizations in seismic environment Classification de vocalises de mammifères marins en environnement sismique Guilment, Thomas Lab-STICC_IMTA_CID_TOMS Laboratoire des sciences et techniques de l'information, de la communication et de la connaissance (Lab-STICC) École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-École Nationale d'Ingénieurs de Brest (ENIB)-Université de Bretagne Sud (UBS)-Université de Brest (UBO)-École Nationale Supérieure de Techniques Avancées Bretagne (ENSTA Bretagne)-Institut Mines-Télécom Paris (IMT)-Centre National de la Recherche Scientifique (CNRS)-Université Bretagne Loire (UBL)-IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT) Département Signal et Communications (IMT Atlantique - SC) IMT Atlantique (IMT Atlantique) Institut Mines-Télécom Paris (IMT)-Institut Mines-Télécom Paris (IMT) Ecole nationale supérieure Mines-Télécom Atlantique Dominique Pastor 2018-06-21 https://theses.hal.science/tel-02090551 https://theses.hal.science/tel-02090551/document https://theses.hal.science/tel-02090551/file/2018IMTA0080_Guilment-Thomas.pdf fr fre HAL CCSD NNT: 2018IMTA0080 tel-02090551 https://theses.hal.science/tel-02090551 https://theses.hal.science/tel-02090551/document https://theses.hal.science/tel-02090551/file/2018IMTA0080_Guilment-Thomas.pdf info:eu-repo/semantics/OpenAccess https://theses.hal.science/tel-02090551 Traitement du signal et de l'image [eess.SP]. Ecole nationale supérieure Mines-Télécom Atlantique, 2018. Français. ⟨NNT : 2018IMTA0080⟩ Classification Marine mammal Seismic environment Sparse representation Machine learning Reconnaissance Mammifères marins Sismique Représentations parcimonieuses Apprentissage automatique [INFO.INFO-TS]Computer Science [cs]/Signal and Image Processing info:eu-repo/semantics/doctoralThesis Theses 2018 ftimtatlantique 2024-01-17T17:27:49Z In partnership with Sercel, the thesis concerns the implementation of algorithms for recognizing the sounds emitted by mysticetes (baleen whales). These sounds can be studiedusing passive acoustic monitoring systems. Sercel, through its seismic activities related to oïl exploration, has its own software to detect and locate underwater sound energy sources. The thesis work therefore consists in adding a recognition module to identify if the detected andlocalized energy corresponds to a possible mysticete. Since seismic shooting campaigns areexpensive, the method used must be able to reduce the probability of false alarms, as recognitioncan invalidate detection. The proposed method is based on dictionary learning. It is dynamic, modular, depends on few parameters and is robust to false alarms. An experiment on five types of vocalizations is presented. We obtain an average recall of 92.1% while rejecting 97.3% of the noises (persistent and transient). In addition, a confidence coefficient is associated with each recognition and allows semi-supervised incremental learning to be achieved. Finally, we propose a method capable of managing detection and recognition together. This "multiclassdetector" best respects the constraints of false alarm management and allows several types of vocalizations to be identified at the same time. This method is well adapted to the industrial context for which it is dedicated. It also opens up very promising prospects in the bioacoustic context. En partenariat avec l’entreprise Sercel, la thèse concerne la mise en œuvre d’algorithmes de reconnaissance des sons émis par les mysticètes (baleines à fanons). Cessons peuvent être étudiés grâce aux systèmes de surveillance par acoustique passive. L’entreprise Sercel, par ses activités sismiques liées à la prospection pétrolière, a son propre logiciel pour détecter et localiser les sources d’énergie sonores sous-marines. Le travail de la thèse consiste dès lors à ajouter un module de reconnaissance pour identifier si l'énergie détectée et ... Doctoral or Postdoctoral Thesis baleen whales Archives ouvertes Hal IMT Atlantique |