Machine Learning for the Birds: Building Your Own Bird Vocalization Classifier

The BirdCLEF+ 2025 competition challenges users to design a classification model that can accurately predict the species of bird from an audio recording. This guide details an approach to build your own bird vocalization classifier that can be used in conjunction with the GBV classifier to classify a wider selection of bird species. The approach employs the same basic techniques described in the Google Research article Separating Birdsong in the Wild for Classification.

Introduction

Scientists use automated systems to study large ecosystems. In the case of forest and jungle areas, autonomous recording units (ARUs) are used to record audio which can be used to help identify different species of animals and insects. This information can be used to develop a better understanding of the distribution of species within a given environment. In the case of birds, Google Research notes in their article ...