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  • Defence R&D Canada Atlantic

    DEFENCE DFENSE&

    Compilation of Marine Mammal PassiveTransients for Aural Classification

    Joe HoodDerek BurnettAkoostix Inc.

    Akoostix Inc.10 Akerley Blvd, Suite 12Dartmouth, NS B3B 1J4

    Project Manager: Dr. Paul C. Hines, 902-426-3100 ext 321

    Contract Number: W7707-078039/001/HAL

    The scientific or technical validity of this Contract Report is entirely the responsibility of the Contractor and thecontents do not necessarily have the approval or endorsement of Defence R&D Canada.

    Contract Report

    DRDC Atlantic CR 2008-287

    April 2009

    Copy No. _____

    Defence Research andDevelopment Canada

    Recherche et dveloppementpour la dfense Canada

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  • Compilation of Marine Mammal Passive Transients for Aural Classification

    Joe Hood Derek Burnett Akoostix Inc. Akoostix Inc. 10 Akerley Blvd, Suite 12 Dartmouth, NS B3B 1J4 Submitted to: Defence Research & Development Canada Atlantic P.O. Box 1012 9 Grove Street Dartmouth, Nova Scotia B2Y 3Z7

    Project Manager: Dr. Paul C. Hines, (902) 426-3100

    Contract number: W7707-078039/001/HAL

    The scientific or technical validity of this Contract Report is entirely the responsibility of the Contractor and the contents do not necessarily have the approval or endorsement of Defence R&D Canada.

    Defence R&D Canada Atlantic Contractor Report DRDC Atlantic CR 2008-287 April 2009

  • Principal Author

    Joe Hood

    President & Chief Technical Officer, Akoostix Inc.

    Approved by

    Dr. Paul Hines

    Project Authority

    Approved for release by

    Dr. Calvin Hyatt

    Chair/Document Review

    Her Majesty the Queen in Right of Canada, as represented by the Minister of National Defence, 2009

    Sa Majest la Reine (en droit du Canada), telle que reprsente par le ministre de la Dfense nationale, 2009

    Original signed by Joe Hood

    Original signed by Dr. Paul Hines

    Original signed by Ron Kuwahara for

  • Abstract ..

    This report documents the work performed to generate a database of marine mammal vocalizations for use with DRDC Atlantics prototype automatic aural classifier. The project involved the selection of appropriate marine mammal and ambient noise data sets, formatting the data, detection processing, extraction of the potential samples, establishment of ground-truth data, post-processing of the data, and classification of each selected sample. Several DRDC Atlantic tools were utilized to perform the variety of tasks, including the Sentinel Acoustic Subsystem (AS) detector, the Acoustic Cetacean Detection Capability (ACDC) application, the Software Tools for Analysis and Research (STAR) suite, and the Omni-Passive Display (OPD) signal processing application. The resulting database contains individually classified samples (hundreds each) of Bowhead, Sperm, Right, and Humpback whales. Each sample exists as an isolated and uniquely identified WAV file. Minimal software development was conducted as part of this contract, although several benefits were realized as the result of synergetic development from separate contracts. The database produced by this contract will directly support the ongoing automated aural classification development.

    Rsum .....

    Le prsent rapport documente le travail accompli aux fins de cration dune base de donnes de vocalisations de mammifres marins devant tre utilise avec le prototype classificateur de signaux sonores de RDDC. Ce projet ncessitait la slection de mammifres marins appropris et dun ensemble de donnes de bruits ambiants, la mise en forme des donnes, la dtection, lextraction dchantillons potentiels, la prise de donnes sur le terrain, le post-traitement des donnes, ainsi que la classification de tous les chantillons retenus. Plusieurs outils de RDDC Atlantique ont t utiliss pour excuter les diverses tches, y compris le systme de dtection Sentinel, lapplication Acoustic Cetacean Detection Capability (ACDC), la suite logicielle danalyse et de recherche (STAR), lapplication de traitement de signal affichage Omni passif (OPD). La base de donnes ainsi cre renferme des chantillons classs individuellement (100 par espce de baleine) pour la baleine borale, le cachalot, la baleine noire et le rorqual bosse. Chaque chantillon existe sous la forme dun fichier .wav distinct et unique. Un travail de dveloppement logiciel minime a t ralis dans le cadre de ce contrat, mais le travail de dveloppement accompli aux termes de plusieurs contrats distincts a globalement t fructueux. La base de donnes cre dans le cadre de ce contrat viendra directement appuyer le travail de dveloppement men en classification automatise de signaux sonores.

    DRDC Atlantic CR 2008-287 i

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    ii DRDC Atlantic CR 2008-287

  • Executive summary

    Compilation of Marine Mammal Passive Transients for Aural Classification

    Joe Hood; Derek Burnett; DRDC Atlantic CR 2008-287; Defence R&D Canada Atlantic; April 2009.

    Introduction or background: This contractor report highlights data analysis in support of the Applied Research Project entitled Automatic Clutter Discrimination Using Aural Cues. The purpose of the analysis was to detect and ground truth vocalizations from several whale (order cetacea) families, and store these detections as .wav files for analysis using DRDCs prototype automatic aural classifier. Vocalizations from four whale types (sperm, bowhead, humpback, and right whale) and anthropogenic false alarms (eg. mechanical noise and RF dropouts) were extracted from both DRDC trial data and public domain data. The bowhead and humpback whales were selected because although they are aurally distinct, automatic classifiers frequently confuse the two. Sperm whale calls are impulsive and represent an easier (baseline) case for the aural classifier. In addition the sperm whale calls provide a measure of performance against anthropogenic false alarms which are impulsive in nature. The right whale was included in the set because it is an endangered species that is resident in local operational waters for which automatic classification would be especially useful to the operational community. The report describes the algorithms used to extract the vocalizations and estimate signal to noise, the annotations that were attached to the data, and the visualization software used in the analysis.

    Results: Approximately 4000 vocalizations and false alarms were extracted and saved as short duration (1-5 s) .wav files. Ground truth was done by subject experts. The original data was carefully annotated and time stamped to allow extended analysis as well as additional ground-truth tests to be performed if required.

    Significance: Present and future military sonar operation must adhere to strict environmental guidelines which include limiting the impact of active sonar on marine mammals. Monitoring marine mammals is labour intensive and requires near-fulltime effort from the operator. Since future military platforms will have to support smaller complements, and near-future operations will have to accommodate additional mission-specific forces, automation of on-board systems is essential. Preliminary testing of DRDCs automatic aural classifier on the vocalizations described in this report is favourable. This classification technique is also well suited to autonomous systems since a much smaller bandwidth is needed to transmit a classification result than to transmit raw acoustic data.

    Future plans: DRDCs prototype automatic aural classifier was originally designed as an active sonar classification tool. This data set of vocalizations will be used to quantify the classifiers performance for passive sonar. In addition to the direct application to marine mammal mitigation, the lessons learned on feature extraction from passive vocalizations can be used to enhance the aural classifier to handle passive transients collected from torpedoes and submarines. This would accelerate its insertion into a detection-classification system within DRDCs sonar test bed (Pleiades).

    DRDC Atlantic CR 2008-287 iii

  • Sommaire .....

    Compilation of Marine Mammal Passive Transients for Aural Classification

    Joe Hood; Derek Burnett; DRDC Atlantic CR 2008-287; R & D pour la dfense Canada Atlantique; April 2009.

    Introduction ou contexte : Lentrepreneur prsente les rsultats danalyse de donnes importantes lappui du projet de recherche applique intitul Automatic Clutter Discrimination Using Aural Cues, un projet dtude portant sur la discrimination automatique dun fouillis dchos parasites au moyen de signaux sonores. Ltude mene avait pour but la dtection et la collecte sur le terrain de donnes de vocalisation produites par plusieurs baleines appartenant lordre des ctacs, ainsi que lenregistrement de ces donnes dans des fichiers portant le suffixe .wav en vue de leur analyse au moyen du prototype de classification automatique de signaux sonores de RDDC. Des donnes de vocalisation provenant de quatre types de baleines cachalot, baleine borale, rorqual bosse et baleine noire et des faux positifs de source anthropique (p. ex. bruits mcaniques et pertes de signal RF) ont t obtenus dessais mens par RDDC et du domaine public. La baleine borale et le rorqual bosse ont t choisis parce que mme si les deux ctacs produisent des signaux sonores distincts, les classificateurs automatiques les confondent souvent. Les appels du cachalot, qui prennent la forme dimpulsions faciles distinguer, constituent une rfrence pour le classificateur; ils permettent de mesurer le rendement par rapport aux faux positifs, qui ont galement l