IEEE Providence Section

The integration of passive acoustic sensors with machine learning enables large-scale, low-cost, non-invasive monitoring of vocal animals. A remaining challenge to the successful deployment of such monitoring systems is in maintaining high classification accuracy across complex real-world soundscapes composed of overlapping calls and variable noise patterns. In this talk, we present an algorithmic pipeline for... Read more →