The Raven-X Software Package. A Scalable High-Performance Computing Framework In Matlab For The Analysis Of Large Bioacoustic Sound Archives.

• Main Authors: Dugan, Peter, Zollweg, John, Roch, Marie, Helble, Tyler, Pitzrick, Michael, Clark, Christopher, Klinck, Holger
• Format: Article in Journal/Newspaper
• Language: unknown
• Published: Zenodo 2018
• Subjects: Silbido; Blue whale; Fin whale; Humpback Whale; minke whale
• Online Access: https://dx.doi.org/10.5281/zenodo.1221416; https://zenodo.org/record/1221416

Raven-X is a software package designed for scalable high-performance computing. The software framework is written in Matlab and uses parallel-distributed computing for the analysis of large bioacoustic sound archives. This application contains various algorithms used for marine mammal sound detection. The various algorithms are available as sub-modules. These include Matched-Filter processing (DTP1D sub-module), Advanced Segmentation Recognition for tonal and pulse trains (ASR sub-module), Whistle Detection and Tracking (Silbido sub-module) and Generalized Power Law (GPL sub-module). These algorithms have a variety of pre-defined methods tuned for detecting Minke Whale, Humpback Whale, Fin Whale, Blue Whale, Elephant Rumbles, Elephant Gunshot and Mid Frequency Sonar. Users with development skills are welcome to create variations of these detectors, or interface new algorithms to the HPC software system. The full version of the software provides a user interface for operation. Operators can select the various data-mining algorithms for processing along with user defined sound archives. A for "some" detectors, a series of feature measures are available to extract for each detected event. Minimum requirement is to have the Matlab Parallel Processing toolbox. The user can select the number of processing nodes from a drop down menu. Raven-X will distribute the selected sounds, detectors and feature measures across the worker nodes, producing a series of output files compatible with the Cornell Raven software. The collaboration of people working on this SW are currently hosting the full version of the tools through BitBucket ([e-mail]:peterdugan68/ravenx-ad.git). Various papers summarizing the technology used in the project can be viewed at https://github.com/peterdugan68/RavenX-ad/wiki/Related-Papers-for-RavenX-project. If you are interested in collaborating on this project please contact ([e-mail]).