Identifying California's Wildlife using Sound
Justin Brashares, Professor
Environmental Science, Policy and Management
Applications for Spring 2026 are closed for this project.
Monitoring the status of wildlife populations is critical to assessing ecosystem health. Rapid advances in machine learning have recently allowed researchers to deploy acoustic recorders that autonomously capture and classify animal vocalizations, such as birds calls. Currently, UC Berkeley is preparing to launching the first ever SoundHub -- an open source data sharing platform for processing animal sound data and species trend monitoring in a single workflow. However, while our bird models are proficient at identifying species, this URAP project aims to build machine learning models for California's non-avian species (primarily frogs and mammals). As a first step, we need to manually listen, identify, and catalogue species calls to build sound libraries that we will use to train machine learning models.
Role: We are seeking multiple students interested in biology and wildlife species identification. The students will identify and verify sound clips for a variety of species including coyotes, dogs, frogs, and crickets in California. Students will be expected to study and memorize animal calls for accurate identification. Sound identification, tagging, and sorting can be done on a student's own computer or a campus computer. The student will train with project scientists and then work independently or as part of a team, while attending weekly group check-ins. Group check-ins will be scheduled for a time slot that works with everyone's schedule.
Qualifications: No experience required to apply! If you are interested and patient, you can learn to ID wildlife calls. However, previous experience in identifying animal calls is a plus. All students must have high attention to detail, patience with repetitive tasks, and interest in wildlife identification. Students can work independently or in teams. Hours per week will be negotiated but at least 6 hours per week is preferred. Remote options available if necessary.
Day-to-day supervisor for this project: Amy Van Scoyoc, Post-Doc
Hours: to be negotiated
Related website: https://nature.berkeley.edu/BrasharesGroup/
Social Sciences Environmental Issues