RAVEN-X: A High Performance Data Mining Toolbox for Bioacoustic Data Analysis
Abstract
The goal of this work is to integrate high performance computing (HPC) technologies and bioacoustics data-mining capabilities by developing a Matlab-based toolset called Raven-X. This toolset will provide a hardware-independent solution, or framework, for processing large acoustic datasets to the research community at no-cost. This goal will be achieved by leveraging prior work done by PI Dugan which successfully deployed a Matlab-based HPC toolset within Cornell University s Bioacoustic Research Program (BRP). The toolset enabled commonly available multi-core computers to process data at accelerated rates to detect and classify whale sounds in large multi-channel sound archives. Through this collaboration, we will expand on this effort which was featured through Mathworks research and industry forums, incorporate new cutting-edge detectors and classifiers, and disseminate Raven-X to the broader bioacoustics community.
Document Details
- Document Type
- DoD Grant Award
- Publication Date
- Nov 23, 2016
- Source ID
- N000141613156
Entities
People
- Peter Dugan
Organizations
- Cornell University
- Office of Naval Research
- United States Navy