Phase 4: DCL System Using Deep Learning Approaches for Land-Based or Ship-Based Real-Time Recognition and Localization of Marine Mammals - Distributed Processing and Big Data Applications

Understand

While the animal bioacoustics community at large is collecting huge amounts of acoustic data at an unprecedented pace, processing these data is problematic.

• Currently in bioacoustics, there is no effective way to achieve high performance computing using commericial off the shelf (COTS) or government off the shelf (GOTS) tools.
• Although several advances have been made in the open source and commercial software community, these offerings either support specific applications that do not integrate well with data formats in bioacoustics or they are too general.
• Furthermore, complex algorithms that use deep learning strategies require special considerations, such as very large libraiers of exemplars (whale sounds) readily available for algorithm training and testing.