ABI Innovation: Computational Methods for Bioacoustic Avian Species Monitoring

Oregon State University, Corvallis OR

Investigators

Abstract

This project focuses on the development of a computational framework for intelligent monitoring of avian species from in situ audio recordings. The system will gather audio from a collection of microphones to automatically and adaptively infer spatio-temporal presence/absence and abundance for different bird species. The system will adaptively seek, request, and incorporate expert feedback to improve the ability to adjust to a new environment. By enabling the automatic collection of bird data at extremely fine temporal resolutions over relatively large spatial scales, we will address two questions of fundamental ecological and conservation importance (1) Can animal behavior buffer species against the effects of environmental changes? Specifically, do birds have the capacity to shift breeding territories in instances of rapid or extreme environmental changes (e.g., weather)? (2) How does loss and fragmentation of tropical forest alter the distributions of bird species? This research will build upon the recently developed Multi-Instance Multi-Label framework from machine learning, and seek to adaptively and actively train species presence/absence and abundance estimation models with the goal of maximizing the learning efficiency while minimizing the human labeling efforts. The system's unique ability to actively identify and adapt to new species (and environments) will greatly reduce the overhead required to deploy and update the bioacoustic monitoring system. This project will provide computational innovations for studying biodiversity as a function of global habitat loss and climate change, contributing significant scientific knowledge about ecosystems and their responses to human activities. The project will also provide a new technology standard for collecting bird population data that could be deployed worldwide for monitoring a diverse and evolving set of species. Research-based education and training opportunities offered by this project will help prepare a new generation of researchers in the emerging area of Ecosystem Informatics at Oregon State University. Outreach activities will 1) involve high school educators in workshops organized by the Oregon Natural Resources Education (ONRE) program, 2) organize annual data challenges/competitions in association with international conferences and workshops, 3)recruit female undergraduates and K-12 students from under-represented groups to careers in computer science and engineering through REU programs. Further information on this project can be found at http://eecs.oregonstate.edu/research/bioacoustics/.