Benjamin Hoffman

BirdCODE detects and classifies bird vocalizations from large audio datasets, enabling large-scale studies of bird communication with improved temporal resolution and species coverage.

The paper maps vocal repertoires to social behaviors in cooperative crows using machine learning and audio-visual data.

This paper describes the BioDCASE data challenge, which aims to advance computational bioacoustics through structured public contests, and reports on its procedures, tasks, and recommendations for community initiatives.

This study uses an AI model to analyze zebra finch vocal interactions and identifies key features of their communication rules.