Comparative bioacoustics: an overview

Welcome
Table of Contents
Title Page
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PREFACE
	Why Write a Bioacoustics Methods eBook?
	An Overview of this Volume
	References
Dedication
List of Contributors
Part I Sound Properties
Sound and Sound Sources
	Abstract
	1. Introduction
	2. Basic Machinery
		2.1. Displacement, Velocity, and Acceleration
		2.2. Force and Laws of Motion
		2.3. Work, Energy, and Power
	3. The Nature of Sound
		3.1. Elasticity and Waves
		3.2. Sound Pressure
		3.3. Sound Intensity and Power
		3.4. The Speed of Sound
	4. The Sound Field: Waves in Time and Space
		4.1. Pressure Fluctuations and Particle Motions
		4.2. The Far Field
			4.2.1. Acoustic Energy
		4.3. Other Sound Fields
	5. Sound Amplitude
		5.1. Logarithmic Machinery
			5.1.1. dB Basics
		5.2. Decibel Arithmetic
		5.3. Comparison of Sound Amplitudes in Air and Water
	6. Sound Sources
		6.1. ‘Small’ and ‘Large’ in Acoustics
		6.2. Monopoles, Dipoles, and Pistons
		6.3. Sound Source Efficiency
	7. Near Fields Around a Sound Source
		7.1. The ‘Flow’ (Reactive) Near Field
		7.2. The Interference Near Field
		7.3. Bioacoustic Examples
	8. Directivity
		8.1. Source Level
	Conclusion
	Practical Advice
	Software Notes
	Conflict of Interest
	Acknowledgements
	References
Propagation of Sound
	Abstract
	1. Introduction
	2. Geometric Attenuation (Geometric Transmission Loss)
	3. Excess Attenuation
	4. Absorption by the Medium
	5. Propagation from one Medium to Another
		5.1. Perpendicular (Normal) Incidence
		5.2. Oblique Incidence and the Critical Angle
	6. Refraction in Stratified Media
	7. Turbulence
	8. Reflection from Large Surfaces
		8.1. The Ground Effect
		8.2. Influence of Surface Properties on the Ground Effect
		8.3. Predicting Effects of Ground Reflection, Absorption, and Turbulence on Sound Propagation
		8.4. Influence of Atmospheric Attenuation and Turbulence on Ground Effect
		8.5. Interference Patterns Under Water
		8.6. General Comments on Ground Effect and Lloyd’s Mirror
		8.7. Standing Waves in a Trapped Sound Field
	9. Scattering and Reflection from Small Targets
		9.1. Scattering in Air
		9.2. Reverberation in Air
		9.3. Reflection from Targets - Echolocation
	10. In the Lab and Field
	Conclusion
	Conflict of Interest
	Acknowledgements
	References
Part II Vocal Production
An Introduction to Laryngeal Biomechanics
	Abstract
	1. Introduction
	2. Myoelastic-aerodynamic Theory of Voice Production
		2.1. Active Movements
		Box 1: Vocal production in frogs.
		2.2. Vocal Fold Morphology
		2.3. Viscoelastic Properties of Vocal Folds
		2.4. Excised Larynx Experiments
			2.4.1. Air Supply
			2.4.2. Measuring Air Flow and Air Pressure
			2.4.3. Mounting the Larynx and Manipulating Adduction and Vocal Fold Tension
			2.4.4. Manipulating Adduction
			2.4.5. Manipulating Vocal Fold Tension
			2.4.6. Audio Recording
			2.4.7. Video Recording
			2.4.8. What can we Learn from Excised Larynx Experiments?
	3. Ultrasonic Vocal Production in Rodents
	Concluding Remarks
	Video Files
	Conflict of Interest
	Acknowledgements
	References
Sound Production and Modification in Birds – Mechanisms, Methodology and Open Questions
	Abstract
	1. Brief History of Exploration of the Avian Sound Source
	2. Sound Production and Modification Requires Coordi-nation of Multiple Motor Systems
	3. Avian Respiration
		3.1. Contribution to Sound Production
		3.2. How we Study Respiratory Contributions to Phonation
		3.3. Respiratory Activity Determines the Coarse Temporal Structure of Song
		3.4. Respiratory Activity Contributes to the Fine Regulation of Airflow
		3.5. Somatosensory Feedback During Song
		3.6. Summary of Some Major Questions for Future Exploration
			3.6.1. Role of Respiratory System in Limiting Temporal Features of Song
			3.6.2. Neural Control and Biomechanics
			3.6.3. Feedback Mechanisms from Respiratory System
			3.6.4. Regulation of Ventilation during Dynamic Behavior Such as Song
	4. Syringeal Mechanisms
		4.1. Functional Morphology of the Vocal Organ
		4.2. Sound Source
		4.3. The Syrinx is a Flow-regulating Valve
		4.4. Muscular Control of the Vocal Organ
		4.5. How we Study the Syrinx During Phonation
			4.5.1. Flow Measurement Technique
			4.5.2. Visualizing the Vibratory Structures During Phonation
			4.5.3. EMG Recording from Syringeal Muscles
			4.5.4. Experimental Manipulation of Syringeal Functions
			4.5.5. Theoretical Approaches and Mechanical Modeling
		4.6. Summary of Some Open Questions
			4.6.1. Muscle Contraction, Force Production in Relation to Electrical Activation
			4.6.2. Synergistic Activity of Syringeal Muscles in Different Contexts
			4.6.3. Motor Units and Use of Superfast and Fast Oxidative Fibers
			4.6.4. Coupling of the Sound Sources and Sound Complexity
			4.6.5. Biomechanics of the Syrinx
			4.6.8. Physiology of Sound Production Across the Diversity in Syrinx Morphology
			4.6.7. Afferent Systems in the Syrinx (Airway Sensors, Muscle Feedback)
	5. Upper Vocal Tract Filtering
		5.1. How We Study Upper Vocal Tract Filtering and How Different Models Emerged?
			5.1.1. Bird Song in a Heliox Atmosphere
			5.1.2. Beak Movements
			5.1.3. X-ray Filming Reveals Dynamic Adjustments in OEC Volume
			5.1.4. Theoretical Approaches Predict Interactions between Upper Vocal Tract and Sound Source
		5.2. Summary of Some Main Unanswered Questions
			5.2.1. Are Beak and OEC Movements Mechanically Coupled?
			5.2.2. How are Upper Vocal Tract Movements Coordinated by the Central Song Control Circuitry?
			5.2.3. For Which Sounds does Coupling between Sound Source and Filter Play a Role?
			5.2.4. Laryngeal-glottal Contributions to Upper Vocal Tract Filtering
	6. Evolutionary Questions
		6.1. How did the Syrinx as a Unique Vocal Organ Evolve?
		6.2. Evolution of Functional Morphology of the Vocal Organ and Song Complexity
		6.3. Vocal Learning, Syringeal Morphology and Acoustic Complexity
	Concluding Remarks
	Conflict of Interest
	Acknowledgements
	References
Source Filter Theory
	Abstract
	1. Introduction
	2. Two Filter Archetypes in Acoustics
		2.1. Excitation of Resonant Systems
		2.2. Helmholtz Resonators
		2.3. Pipe Resonators
	3. Sound Sources and Filters in Human and Animal Phonation
		3.1. Sound Radiated from the Lips Reflects also Filter Properties
		3.2. Estimating Filter Characteristics
	Online Sources
	Conflict of Interest
	Acknowledgements
	References
Part III Sound Analysis in Bioacoustics
Acoustic Preference Methods: Assessing Mates
	Abstract
	1. Introduction
		1.1. How Mating Preferences Guide Mate Choice
		1.2. What is this Chapter about?
		1.3. Are Acoustic Signals Special?
	2. General Conceptual Issues: The Role of Signals in Mate Choice
		2.1. Detection, Localization and Recognition
		2.2. Discrimination versus Preference
		2.3. Mating Preference is not the Same as Mate Choice
	3. Preference Testing
		3.1. Asking the Right Questions: Combining Observations and Experiments
		3.2. Single Stimulus, Sequential or Simultaneous Choice Tests?
	4. Review of Methods for Acoustic Preference Testing
		4.1. Phonotaxis Tests
		4.2. Loudspeaker Approach Tests
			4.2.1. Variant: T, Y- and Multi-arm-mazes
			4.2.2. Variant: Walking Compensators and Treadmills
			4.2.3. Variant: Nesting Cavity Choice Tests
		4.3. Other Behavioral Responses to Playback
			4.3.1. Vocal Responses/Calling Assays
			4.3.2. Copulation Solicitation (CSDs) Assays
			4.3.3. Nest Building Assay
		4.4. Physiological Measures
			4.4.1. Heart Rate
			4.4.2. Stimulation of Hormone Profiles through Song Playback
			4.4.3. Maternal Allocation
			4.4.4. Functional Magnetic Resonance Imaging (fMRI)
		4.5. Active Choice Tests
			4.5.1. Playback Chambers
			4.5.2. Operant Preference Techniques (e.g. Key Pecking, Perch Hopping)
		4.6. Live Stimulus Subject(s)
	5. Avoiding Confounds – General Caveats
		5.1. Housing & Rearing
		5.2. Acclimation Times
		5.3. Pseudoreplication
		5.4. Order Effects
		5.5. Audience Effects and Eavesdropping
		5.6. Experimenter Biases
		5.7. Learning (Before and During Experiments, See Also Order Effects)
		5.8. Multimodality
		5.9. Stimulus Preparation
		Box 1: Internal and external validation of an experiment.
		Box 2: Suggested further reading.
	Conflict of Interest
	Acknowledgements
	References
Filtering in Bioacoustics
	Abstract
	1. Introduction
	2. Anatomy of a Filter
		2.1. Gain Function
		2.2. Other Filter Characteristics
		2.3. Trade-Offs in Filter Performance
		2.4. Response to Transients
		2.5. Analog Filter Types
	3. Aliasing
		3.1. The Nyquist Frequency
		3.2. Sampling With and Without Filtering
		3.3. Analog, Anti-Alias Filtering
		3.4. Filter Operation
			3.4.1. Sampling and Filtering at 48 kHz
			3.4.2. Sampling and Filtering at 24 kHz
			3.4.3. Anti-Image Filtering in D/A Conversion
	4. Comparing Analog and Digital Filters
		4.1. Analog Components are Passive or Active
		4.2. Digital Filters
	5. Designs and Functions of Digital Filters
		5.1. Filter Impulse Response
		5.2. FIR Versus IIR Filters
		5.3. Filtering in the Frequency Domain
		5.4. Cascaded Filters and Repeated Filtering
	6. Applications of Digital Filters
		6.1. Zero-Delay Filtering
		6.2. Simulating Environmental Effects
			6.2.1. Echo
			6.2.2. Attenuation and Reverberation
		6.3. Matched-Filter Techniques
			6.3.1. Signal Detection
			6.3.2. Noise Gating
	7. Removing DC and AC Contamination
	Conclusion
		Summary
		Practical Advice
		The Disappearing Voice of the Southern Weaver Bird
	Software Notes
	Conflict of Interest
	Acknowledgements
	References
Nonlinear Dynamics and Temporal Analysis
	Abstract
	1. Introduction
	2. Nonlinear Dynamics and Attractors
	3. Methods
		3.1. Delay-Coordinate Space
		3.2. False Nearest Neighbor Analysis
		3.3. DVS Modeling and Nonlinearity Measure
		3.4. Surrogate Analysis
	4. Applications
		4.1. Pathological Voice
		4.2. Macaque Scream
		4.3. Dog Bark
	Discussions
	Sound Files
	Conflict of Interest
	Acknowledgements
	References
Hidden Markov Model Signal Classification
	Abstract
	1. Introduction
		1.1. Overview of Automated Bioacoustics Tasks
			1.1.1. Detection
			1.1.2. Classification
			1.1.3. Clustering
		1.2. Example Applications
			1.2.1. Signal Detection
			1.2.2. Call/Vocalization Detection
			1.2.3. Call Classification
			1.2.4. Species Classification
			1.2.5. Individual Identification
			1.2.6. Unsupervised Clustering of Calls for Repertoire Analysis
			1.2.7. Unsupervised Clustering of Individuals
			1.2.8. Interactive Automatic Annotation System for Vocalization Labeling
			1.2.9. Acoustic Censusing
		1.3. Broad Overview of Classification Models
			1.3.1. Simple Statistical Models
			1.3.2. Template Matching Models
				1.3.2.1. Spectrogram Cross-Correlation
				1.3.2.2. Matched Filtering
			1.3.3. Non-temporal Models of Signal Spectrum
			1.3.4. Neural Network and Other Machine Learning Models
			1.3.5. Dynamic Time Warping
			1.3.6. Hidden Markov Models
		1.4. Acoustic Characteristics for Model Selection
			1.4.1. Temporal and Spectral Resolution
			1.4.2. Variability Across Individuals
			1.4.3. Acoustic Environment
	2. Perceptually Relevant Feature Selection and Extraction
		2.1. Sound Production and Perception Models
		2.2. The Spectral and Cepstral Domains
		2.3. Nonstationarity of Bioacoustic Signals
		2.4. Perceptual Modeling for Bioacoustics
			2.4.1. Greenwood Frequency Cepstral Coefficients (GFCC)
			2.4.2. Generalized Linear Prediction Coefficients (gPLP)
		2.5. Feature Selection and Transformation versus Feature Learning
	3. Statistical Classification Using Hidden Markov Models
		HMM Recognition
		HMM Evaluation
		HMM Training
		3.1. Step-by-step Guide to Using HMMs for Acoustic Pattern Classification
		3.2. Language Modeling and Vocal Sequences
		3.3. Important Elements of HMMs for Time-series Classification
		Feature Selection
		Framing, Frame Size, and Step Size
		Number of States and HMM Transition Topology
		Use of Data – Development Sets and Cross Validation
		3.4. Using HMMs for Detection and Alignment
		3.5. Using HMMs for Clustering
		3.6. Example Application: Acoustic Censusing
	Conclusion
		Summary
		Software Notes
	Conflict of Interest
	Acknowledgements
	References
Classifying Animal Sounds with Neural Networks
	Abstract
	1. Introduction
		1.1. Classifying Sounds Subjectively
		1.2. Naturalistic Classification of Sounds
		1.3. Classifying Sounds Objectively
		1.4. Using Connectionist Models to Classify Sounds
	2. Neural Network Basics
		2.1. Simulating Neural Processing
		2.2. Representing Inputs: Transforming Real-World Events into Vectors
		2.3. Single-Layer Neural Networks
		2.4. Multi-Layer Neural Networks
		2.5. Training Neural Networks
		2.6. Advantages and Disadvantages of Neural Networks
	3. Using Neural Networks to Sort Vocalizations
		3.1. Categorizing Chickadee Call Sounds with a Multi-Layer Neural Network
		3.2. Sorting Gradations in False Killer Whale Sounds with a Self-Organizing Map
		3.3. Describing the Temporal Dynamics of Humpback Whale Songs with Self-Organizing Maps
			3.3.1. Humpback Whale Song Content and Structure
			3.3.2. Classifying Sounds within Humpback Whale Songs
			3.3.3. Classifying Sequences within Humpback Whale Songs
	4. Using Neural Networks to Understand How Animals Classify Sounds
		4.1. Simulating Distance Estimation by Whales with a Single-Layer Perceptron
		4.2. Simulating Note Discrimination Learning by Chickadees with a Single-Layer Perceptron
	Conclusion
		Summary
		Practical Advice
		Future Prospects
	Software Notes
	Conflict of Interest
	Acknowledgements
	References
Part IV Sound Recording and Archiving
Sound Archives and Media Specimens in the 21st Century
	Abstract
	Introduction: What is a ‘Media Specimen’?
	Sound/Media Archives and Their Value to Modern Biological Research
	The Digital Revolution and the Changing Face of Sound Archives
		Permanence of Digital Files and Archival Standards
		Accessibility and Changing Expectations
		The Internet Revolution and Citizen Science
	Conclusion and Recommendations
	Conflict of Interest
	Acknowledgements
	References