bioacoustics-resource-page

Bioacoustics Resource Page

A list curated by Sam Lapp and the Kitzes Lab

hint: bookmark this page :)

Bioacoustics workshops & guides

• Bioacoustics Classifier Bootcamp: Course Materials
  • 10-week course on developing machine learning classifiers for PAM
  • resources, assignments, and links to slides, recordings, and summaries
• Classifiers 101 guide - machine learning classification for bioacoustics, for beginners
• GitHub - leabouffaut/bioacoustics Helpful code examples for bioacoustics in Python
• Bioacoustic Cookbook: example scripts, notebooks, and templates for common tasks
• Conference workshops on Passive Acoustic Monitoring
  • ESA 2023 - Bioacoustic Monitoring Workshop
  • ESA 2024 - Automated Bioacoustic Surveys 1: Recorder preparation, field deployments, and introductory analysis and inference
  • ESA 2024 - Automated Bioacoustic Surveys 2: Machine learning classifiers, advanced statistics, and sound source localization
  • AOS workshop - advanced bioacoustic monitoring
    • associated resources, notebooks, q\&a google doc

Other bioacoustics educational materials

• BioacousTalks - biweekly lectures by bioacoustics researchers (recordings on YouTube!)
• Lecture series from Computer Vision for Ecology workshop - YouTube
  • Computer Vision 4 Ecology: Glossary
  • AI Coding for Effective Science
• Review paper on computational bioacoustics with deep learning by Dan Stowell

• Kaggle - examples of how people solved ML bioacoustics tasks (e.g. blog posts)

  General data science lessons

• Data science & computing cheat sheet - an informal guide to the “hidden curriculum” of tools needed to do computational ecology, plus our favorite commands
• Data Science Lessons – materials for two-day introductory data science workshops
  • see in particular the ~2-hour self-paced tutorial on git and GitHub
• Software Carpentry lessons – introductory tutorials on computing and data science

• The Practice of Reproducible Research – online version of book edited by Justin Kitzes on reproducibility, see in particular the Basic Reproducible Workflow Template chapter

  Data and Software Compilations

• Github Bioacoustics datasets list (open-source, the most complete list)
  • Spreadsheet of annotated bird sound datasets
  • Another list of annotated bioacoustics datasets from Lila.bc
• Benchmark datasets (for comparing machine learning model performance):
  • BEANS detection and classification benchmark
  • BirdSET bird classification benchmark
• Bioacoustics software list: current software for a wide variety of bioacoustics tasks

Community Forums

• WILDLABS.net – large online community with ecology/conservation tech discussions, including an acoustics-specific group
• Bioacoustics Stack Exchange - Q\&A with the bioacoustics community
• AI for Conservation Slack - an active and welcoming community. To join, email aiforconservation@gmail.com
• Bioacoustics feed on Bluesky

OpenSoundscape

Our lab’s open-source package for bioacoustic analysis

• Documentation and tutorials
• Classifiers 101 guide
• GitHub open-source code base
• Bioacoustic Cookbook: example scripts, notebooks, and templates for common tasks
• Bioacoustics Model Zoo: pretrained ML models compatible with OpenSoundscape
• Google Colab: run Python notebooks on the cloud

Examples: real-world applications of OpenSoundscape

• Underwater vocalizations of the endangered Sierra Nevada Yellow-legged frog
• Canada Warbler breeding habitat use
• Predictors of Great Horned Owl habitat use and successful reproduction
• Eastern whip-poor-will occupancy across forest management regimes
• Evaluating unmarked abundance models with machine-learning classification of PAM data
• Detecting Ruffed Grouse drumming
• RIBBIT: a method for detecting calls with repeated elements
• Automated detection of gunshots in tropical forests using convolutional neural networks

Field deployment guidelines

• Terrestrial ABMI Autonomous Recording Unit (ARU) and Remote Camera Trap Protocols
• a2o - deployment manual for solar powered acoustic sensors
• Passive acoustic monitoring in ecology and conservation (WWF)

ARUs and other hardware

• AudioMoth guide: detailed guide for all steps of preparing and deploying AudioMoth recorders for acoustic monitoring, written by Tessa Rhinehart in our lab (Open Acoustic Devices now has a shorter guide based on this material on their website)
• AudioMoth and Song Meter Micro Battery Testing – information on the expected battery life of these two recorders for a variety of sample rates, gain settings, device temperatures, and battery types, written by Nick Stahlman in our lab
• AudioMoth Performance Testing – information on the acoustic performance of AudioMoth recorders in different orientations and housing options, written by Sam Lapp in our lab
• Open Acoustic Devices : maker of the AudioMoth field recorder

  • AudioMoth info page - [AudioMoth

    Open Acoustic Devices](https://www.openacousticdevices.info/audiomoth)

  • Open Acoustic Devices GroupGets page: group purchases for AudioMoths are posted regularly; recent component shortages mean they are harder to get
  • see also the Hill et al 2018 paper
  • AudioMoth configuration and flash apps
• GitHub for Raspberry Pi SD card aggregators (Swallows)

Annotation

• Audacity: a desktop program for listening to audio data and viewing spectrograms
• Kitzes Lab’s Annotation Guide step-by-step guide for annotating audio in Raven Pro/Lite
• Raven Pro subscription-based annotation software
• Raven Lite free version of Raven Pro but with somewhat limited functionality,
  • e.g., can only use one free text entry column for annotations in an annotation table
• Whombat an open-source annotation tool currently under development

Classification / Analysis packages

• Classifiers 101 guide: step-by-step guide on developing machine learning recognizers for biological sounds
• OpenSoundscape: our lab’s Python package for bioacoustic analyses and recognizer development
• Bioacoustics Model Zoo: suite of pretrained ML models compatible with OpenSoundscape
• Batdetect2: bat detection and classification toolkit
• Koogu: toolkit for training bioacoustic classifiers with PyTorch
• BirdNET: global bird classification model by the Cornell Lab of Ornithology
• Perch: Google global bird vocalization classifier; see variants for coral reefs and whales
• Kaleidoscope Pro: pre-trained classifier for bats; other classification methods available. Pricey/paid software
• https://github.com/kitzeslab/r-ribbit Implementation of the RIBBIT method (identify calls with repeated structure) for R (Note: we don’t update it, so we recommend using Python & OpenSoundscape)
• Agile modeling tutorial notebook resources for quickly creating a classifier, including using embedding search to find training samples, see also readme
  • Note: this functionality is being ported to the perch-hoplite repo

Occupancy modeling

• Continuous-score occupancy model - a new approach for interpretation of deep learning model outputs
• From species identification to occupancy modeling - a workflow and demonstration of how to run a machine learning classifier (here for camera traps) and incorporate the results into an occupancy model

Other resources

• Graphic Design for Ecology resources
• Sound Calculator decibel, voltage, and distance conversions

Demos

• A2O embedding Search demo
  • demo search for Eastern Whipbird