Detection and Classification of Whale Acoustic Signals
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Acoustic Monitoring of Beluga Whale Interactions with Cook Inlet Tidal Energy Project De-Ee0002657
< U.S. DEPARTMENT OF ENERGY ACOUSTIC MONITORING OF BELUGA WHALE INTERACTIONS WITH COOK INLET TIDAL ENERGY PROJECT DE-EE0002657 FINAL TECHNICAL REPORT February 5, 2014 ORPC Alaska, LLC 725 Christensen Dr., Suite 6 Anchorage, AK 99501 Phone (207) 772-7707 www.orpc.co ORPC Alaska, LLC: DE-EE0002657 Acoustic Monitoring of Beluga Whale Interactions with Cook Inlet Tidal Energy Project February 5, 2014 Award Number: DE-EE0002657 Recipient: ORPC Alaska, LLC Project Title: Acoustic Monitoring of Beluga Whale Interactions with the Cook Inlet Tidal Energy Project PI: Monty Worthington Project Team: LGL Alaska Research Associates, Tamara McGuire University of Alaska Anchorage, Jennifer Burns TerraSond, Ltd Greeneridge Science Inc., Charles Greene EXECUTIVE SUMMARY Cook Inlet, Alaska is home to some of the greatest tidal energy resources in the U.S., as well as an endangered population of beluga whales (Delphinapterus leucas). Successfully permitting and operating a tidal power project in Cook Inlet requires a biological assessment of the potential and realized effects of the physical presence and sound footprint of tidal turbines on the distribution, relative abundance, and behavior of Cook Inlet beluga whales. ORPC Alaska, working with the Project Team—LGL Alaska Research Associates, University of Alaska Anchorage, TerraSond, and Greeneridge Science—undertook the following U.S. Department of Energy (DOE) study to characterize beluga whales in Cook Inlet – Acoustic Monitoring of Beluga Whale Interactions with the Cook Inlet Tidal Energy Project (Project). ORPC Alaska, LLC, is a wholly-owned subsidiary of Ocean Renewable Power Company, LLC, (collectively, ORPC). ORPC is a global leader in the development of hydrokinetic power systems and eco-conscious projects that harness the power of ocean and river currents to create clean, predictable renewable energy. -
A Thesis Entitled Nocturnal Bird Call Recognition System for Wind Farm
A Thesis entitled Nocturnal Bird Call Recognition System for Wind Farm Applications by Selin A. Bastas Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Electrical Engineering _______________________________________ Dr. Mohsin M. Jamali, Committee Chair _______________________________________ Dr. Junghwan Kim, Committee Member _______________________________________ Dr. Sonmez Sahutoglu, Committee Member _______________________________________ Dr. Patricia R. Komuniecki, Dean College of Graduate Studies The University of Toledo December 2011 Copyright 2011, Selin A. Bastas. This document is copyrighted material. Under copyright law, no parts of this document may be reproduced without the expressed permission of the author. An Abstract of Nocturnal Bird Call Recognition System for Wind Farm Applications by Selin A. Bastas Submitted to the Graduate Faculty as partial fulfillment of the requirements for the Master of Science Degree in Electrical Engineering The University of Toledo December 2011 Interaction of birds with wind turbines has become an important public policy issue. Acoustic monitoring of birds in the vicinity of wind turbines can address this important public policy issue. The identification of nocturnal bird flight calls is also important for various applications such as ornithological studies and acoustic monitoring to prevent the negative effects of wind farms, human made structures and devices on birds. Wind turbines may have negative impact on bird population. Therefore, the development of an acoustic monitoring system is critical for the study of bird behavior. This work can be employed by wildlife biologist for developing mitigation techniques for both on- shore/off-shore wind farm applications and to address bird strike issues at airports. -
The Articulatory and Acoustic Characteristics of Polish Sibilants and Their Consequences for Diachronic Change
The articulatory and acoustic characteristics of Polish sibilants and their consequences for diachronic change Veronique´ Bukmaier & Jonathan Harrington Institute of Phonetics and Speech Processing, University of Munich, Germany [email protected] [email protected] The study is concerned with the relative synchronic stability of three contrastive sibilant fricatives /s ʂɕ/ in Polish. Tongue movement data were collected from nine first-language Polish speakers producing symmetrical real and non-word CVCV sequences in three vowel contexts. A Gaussian model was used to classify the sibilants from spectral information in the noise and from formant frequencies at vowel onset. The physiological analysis showed an almost complete separation between /s ʂɕ/ on tongue-tip parameters. The acoustic analysis showed that the greater energy at higher frequencies distinguished /s/ in the fricative noise from the other two sibilant categories. The most salient information at vowel onset was for /ɕ/, which also had a strong palatalizing effect on the following vowel. Whereas either the noise or vowel onset was largely sufficient for the identification of /s ɕ/ respectively, both sets of cues were necessary to separate /ʂ/ from /s ɕ/. The greater synchronic instability of /ʂ/ may derive from its high articulatory complexity coupled with its comparatively low acoustic salience. The data also suggest that the relatively late stage of /ʂ/ acquisition by children may come about because of the weak acoustic information in the vowel for its distinction from /s/. 1 Introduction While there have been many studies in the last 30 years on the acoustic (Evers, Reetz & Lahiri 1998, Jongman, Wayland & Wong 2000,Nowak2006, Shadle 2006, Cheon & Anderson 2008, Maniwa, Jongman & Wade 2009), perceptual (McGuire 2007, Cheon & Anderson 2008,Li et al. -
ECHO Program Salish Sea Ambient Noise Evaluation
Vancouver Fraser Port Authority Salish Sea Ambient Noise Evaluation 2016–2017 ECHO Program Study Summary This study was undertaken for Vancouver Fraser Port Authority’s Enhancing Cetacean Habitat and Observation (ECHO) Program to analyze regional acoustic data collected over two years (2016–2017) at three sites in the Salish Sea: Haro Strait, Boundary Pass and the Strait of Georgia. These sites were selected by the ECHO Program to be representative of three sub-areas of interest in the region in important habitat for marine mammals, including southern resident killer whales (SRKW). This summary document describes how and why the project was conducted, its key findings and conclusions. What questions was the study trying to answer? The ambient noise evaluation study investigated the following questions: What were the variabilities and/or trends in ambient noise over time and for each site, and did these hold true for all three sites? What key factors affected ambient noise differences and variability at each site? What are the key requirements for future monitoring of ambient noise to better understand the contribution of commercial vessel traffic to ambient noise levels, and how ambient noise may be monitored in the future? Who conducted the project? JASCO Applied Sciences (Canada) Ltd., SMRU Consulting North America, and the Coastal & Ocean Resource Analysis Laboratory (CORAL) of University of Victoria were collaboratively retained by the port authority to conduct the study. All three organizations were involved in data collection and analysis at one or more of the three study sites over the two-year time frame of acoustic data collection. -
Music Information Retrieval Using Social Tags and Audio
A Survey of Audio-Based Music Classification and Annotation Zhouyu Fu, Guojun Lu, Kai Ming Ting, and Dengsheng Zhang IEEE Trans. on Multimedia, vol. 13, no. 2, April 2011 presenter : Yin-Tzu Lin (阿孜孜^.^) 2011/08 Types of Music Representation • Music Notation – Scores – Like text with formatting symbolic • Time-stamped events – E.g. Midi – Like unformatted text • Audio – E.g. CD, MP3 – Like speech 2 Image from: http://en.wikipedia.org/wiki/Graphic_notation Inspired by Prof. Shigeki Sagayama’s talk and Donald Byrd’s slide Intra-Song Info Retrieval Composition Arrangement probabilistic Music Theory Symbolic inverse problem Learning Score Transcription MIDI Conversion Accompaniment Melody Extraction Performer Structural Segmentation Synthesize Key Detection Chord Detection Rhythm Pattern Tempo/Beat Extraction Modified speed Onset Detection Modified timbre Modified pitch Separation Audio 3 Inspired by Prof. Shigeki Sagayama’s talk Inter-Song Info Retrieval • Generic-similar – Music Classification • Genre, Artist, Mood, Emotion… Music Database – Tag Classification(Music Annotation) – Recommendation • Specific-similar – Query by Singing/Humming – Cover Song Identification – Score Following 4 Classification Tasks • Genre Classification • Mood Classification • Artist Identification • Instrument Recognition • Music Annotation 5 Paper Outline • Audio Features – Low-level features – Middle-level features – Song-level feature representations • Classifiers Learning • Classification Task • Future Research Issues 6 Audio Features 7 Low-level Features -
Selecting Proper Features and Classifiers for Accurate Identification of Musical Instruments
International Journal of Machine Learning and Computing, Vol. 3, No. 2, April 2013 Selecting Proper Features and Classifiers for Accurate Identification of Musical Instruments D. M. Chandwadkar and M. S. Sutaone y The performance of the learning procedure is evaluated Abstract—Selection of effective feature set and proper by classifying new sound samples (cross-validation). classifier is a challenging task in problems where machine One of the most crucial aspects in the above procedure of learning techniques are used. In automatic identification of instrument classification is to find the right features [2] and musical instruments also it is very crucial to find the right set of classifiers. Most of the research on audio signal processing features and accurate classifier. In this paper, the role of various features with different classifiers on automatic has been focusing on speech recognition and speaker identification of musical instruments is discussed. Piano, identification. Few features used for these can be directly acoustic guitar, xylophone and violin are identified using applied to solve the instrument classification problem. various features and classifiers. Spectral features like spectral In this paper, feature extraction and selection for centroid, spectral slope, spectral spread, spectral kurtosis, instrument classification using machine learning techniques spectral skewness and spectral roll-off are used along with autocorrelation coefficients and Mel Frequency Cepstral is considered. Four instruments: piano, acoustic guitar, Coefficients (MFCC) for this purpose. The dependence of xylophone and violin are identified using various features instrument identification accuracy on these features is studied and classifiers. A number of spectral features, MFCCs, and for different classifiers. Decision trees, k nearest neighbour autocorrelation coefficients are used. -
Report of the NOAA Workshop on Anthropogenic Sound and Marine Mammals, 19-20 February 2004
Report of the NOAA Workshop on Anthropogenic Sound and Marine Mammals, 19-20 February 2004 Jay Barlow and Roger Gentry, Conveners INTRODUCTION The effect of man-made sounds on marine mammals has become a clear conservation issue. Strong evidence exists that military sonar has caused the strandings of beaked whales in several locations (Frantzis 1998; Anon. 2001). Seismic surveys using airguns may be also implicated in at least one beaked whale stranding (Peterson 2003). Shipping adds another source of noise that has been increasing with the size of ships and global trade. Overall, global ocean noise levels appear to be increasing as a result of human activities, and off central California, sound pressure levels at low frequencies have increased by 10 dB (a 10-fold increase) from the 1960s to the 1990s (Andrew et al. 2002). Within the U.S., the conservation implications of anthropogenic noise are being researched by the Navy, the Minerals Management Service (MMS), and the National Science Foundation (NSF); however, the sources of man-made sound are broader than the concerns of these agencies. The National Oceanographic and Atmospheric Administration (NOAA) has a broader mandate for stewardship of marine mammals and other marine resources than any other federal agency. Therefore, there is a growing need for NOAA to take an active role in research on the effects of anthropogenic sounds on marine mammals and, indeed, on the entire marine ecosystem. This workshop was organized to provide background information needed by NOAA for developing a research program that will address issues of anthropogenic sound in the world's oceans. -
Diel and Spatial Dependence of Humpback Song and Non-Song Vocalizations in Fish Spawning Ground
remote sensing Article Diel and Spatial Dependence of Humpback Song and Non-Song Vocalizations in Fish Spawning Ground Wei Huang, Delin Wang and Purnima Ratilal * Department of Electrical and Computer Engineering, Northeastern University, 360 Huntington Ave., Boston, MA 02115, USA; [email protected] (W.H.); [email protected] (D.W.) * Correspondence: [email protected]; Tel.: +1-617-373-8458 Academic Editors: Nicholas Makris, Xiaofeng Li and Prasad S. Thenkabail Received: 10 June 2016; Accepted: 23 August 2016; Published: 30 August 2016 Abstract: The vocalization behavior of humpback whales was monitored over vast areas of the Gulf of Maine using the passive ocean acoustic waveguide remote sensing technique (POAWRS) over multiple diel cycles in Fall 2006. The humpback vocalizations comprised of both song and non-song are analyzed. The song vocalizations, composed of highly structured and repeatable set of phrases, are characterized by inter-pulse intervals of 3.5 ± 1.8 s. Songs were detected throughout the diel cycle, occuring roughly 40% during the day and 60% during the night. The humpback non-song vocalizations, dominated by shorter duration (≤3 s) downsweep and bow-shaped moans, as well as a small fraction of longer duration (∼5 s) cries, have significantly larger mean and more variable inter-pulse intervals of 14.2 ± 11 s. The non-song vocalizations were detected at night with negligible detections during the day, implying they probably function as nighttime communication signals. The humpback song and non-song vocalizations are separately localized using the moving array triangulation and array invariant techniques. The humpback song and non-song moan calls are both consistently localized to a dense area on northeastern Georges Bank and a less dense region extended from Franklin Basin to the Great South Channel. -
The Subjective Size of Melodic Intervals Over a Two-Octave Range
JournalPsychonomic Bulletin & Review 2005, ??12 (?),(6), ???-???1068-1075 The subjective size of melodic intervals over a two-octave range FRANK A. RUSSO and WILLIAM FORDE THOMPSON University of Toronto, Mississauga, Ontario, Canada Musically trained and untrained participants provided magnitude estimates of the size of melodic intervals. Each interval was formed by a sequence of two pitches that differed by between 50 cents (one half of a semitone) and 2,400 cents (two octaves) and was presented in a high or a low pitch register and in an ascending or a descending direction. Estimates were larger for intervals in the high pitch register than for those in the low pitch register and for descending intervals than for ascending intervals. Ascending intervals were perceived as larger than descending intervals when presented in a high pitch register, but descending intervals were perceived as larger than ascending intervals when presented in a low pitch register. For intervals up to an octave in size, differentiation of intervals was greater for trained listeners than for untrained listeners. We discuss the implications for psychophysi- cal pitch scales and models of music perception. Sensitivity to relations between pitches, called relative scale describes the most basic model of pitch. Category pitch, is fundamental to music experience and is the basis labels associated with intervals assume a logarithmic re- of the concept of a musical interval. A musical interval lation between pitch height and frequency; that is, inter- is created when two tones are sounded simultaneously or vals spanning the same log frequency are associated with sequentially. They are experienced as large or small and as equivalent category labels, regardless of transposition. -
Passive Acoustic Monitoring for Marine Mammals in the Jacksonville Range Complex 2010
Passive Acoustic Monitoring for Marine Mammals in the Jacksonville Range Complex 2010 Sarah C. Johnson, Ana Širović, Jasmine S. Buccowich, Amanda J. Debich, Lauren K. Roche, Bruce Thayre, Sean M. Wiggins, John A. Hildebrand, Lynne E. W. Hodge and Andrew J. Read Marine Physical Laboratory Scripps Institution of Oceanography University of California San Diego La Jolla, CA 92037 Minke Whale, Photo by Amanda J. Debich MPL TECHNICAL MEMORANDUM # 548 February 2014 Prepared for US Fleet Forces Command and submitted to Naval Facilities Engineering Command (NAVFAC) Atlantic, under Contract No. N62470-10D-3011 issued to HDR, Inc. 1 Suggested Citation: SC Johnson, A Širović, JS Buccowich, AJ Debich, LK Roche, B Thayre, SM Wiggins, JA Hildebrand, LEW Hodge, and AJ Read. 2014. Passive Acoustic Monitoring for Marine Mammals in the Jacksonville Range Complex 2010. Final Report. Submitted to Naval Facilities Engineering Command (NAVFAC) Atlantic, Norfolk, Virginia, under Contract No. N62470-10D-3011 issued to HDR, Inc. Individual technical reports of the HARP deployments are available at: http://www.navymarinespeciesmonitoring.us/reading-room/ 2 Table of Contents Executive Summary ....................................................................................................................................... 4 Project Background ....................................................................................................................................... 5 Methods ....................................................................................................................................................... -
Visual and Passive Acoustic Observations of Blue Whale Trios from Two Distinct Populations
Received: 27 March 2019 Revised: 13 August 2019 Accepted: 13 August 2019 DOI: 10.1111/mms.12643 NOTE Visual and passive acoustic observations of blue whale trios from two distinct populations Elena Schall1,2 | Lucia Di Iorio3 | Catherine Berchok4 | Diego Filún1,2 | Luis Bedriñana-Romano1,6 | Susannah J. Buchan7,8,9 | Ilse Van Opzeeland2,10 | Richard Sears5 | Rodrigo Hucke-Gaete1,6 1NGO Centro Ballena Azul, Universidad Austral de Chile, Valdivia, Chile 2Physical Oceanography of the Polar Seas, Alfred Wegener Institute for Polar and Marine Research, Bremerhaven, Germany 3Chorus Research Institute, Grenoble Institute of Engineering, Grenoble, France 4Marine Mammal Laboratory, Alaska Fisheries Science Center/NOAA, Seattle, Washington 5Mingan Island Cetacean Study, Saint-Lambert, Canada 6Instituto de Ciencias Marinas y Limnológicas, Universidad Austral de Chile, Valdivia, Chile 7Center for Oceanographic Research COPAS Sur-Austral, University of Concepción, Concepción, Chile 8Centro de Estudios Avanzados en Zonas Aridas (CEAZA), Coquimbo, Chile 9Woods Hole Oceanographic Institution, Biology Department, Woods Hole, Massachusetts 10Helmholtz Institute for Functional Marine Biodiversity, Carl von Ossietzky University Oldenburg, Oldenburg, Germany Correspondence Elena Schall, Alfred Wegener Institute for Polar and Marine Research, Klußmannstraße 3d, 27570 Bremerhaven, Germany. Email: [email protected] Blue whale populations from both hemispheres are thought to undertake annual migrations between high latitude feeding grounds and low latitude breeding -
Impacts of Environment-Dependent Acoustic Propagation on Passive Acoustic Monitoring of Cetaceans
IMPACTS OF ENVIRONMENT-DEPENDENT ACOUSTIC PROPAGATION ON PASSIVE ACOUSTIC MONITORING OF CETACEANS by Carolyn M. Binder Submitted in partial fulfillment of the requirements for the degree of Doctor of Philosophy at Dalhousie University Halifax, Nova Scotia July 2017 DRDC-RDDC-2017-P060 c Her Majesty the Queen in Right of Canada, Minister of National Defence, 2017 For my family. I couldn’t have done this without your support, dedication, and love. ii TABLE OF CONTENTS List of Tables ..................................... vii List of Figures .................................... ix Abstract ........................................ xiv List of Abbreviations and Symbols Used ...................... xv Acknowledgements ................................. xix Chapter 1 Introduction ............................ 1 1.1 Literature Review .............................. 1 1.2 Investigating the Impacts of Environment- Dependent Propagation on an Automated Aural Classifier ......................... 4 1.2.1 Thesis Outline ........................... 6 Chapter 2 Automated Aural Classifier and Performance Metrics ..... 8 2.1 The Aural Classifier ............................. 9 2.1.1 Validation of Classifier Performance ............... 10 2.2 Performance Metrics ............................ 13 Chapter 3 Biogenic and Synthetic Vocalization Data Set .......... 18 3.1 Biogenic Whale Calls ............................ 18 3.2 Synthetic Whale Calls ............................ 21 3.2.1 Comparison of Synthetic Calls with Biogenic Whale Calls .... 23 3.3 Conditioning and