orcadata

This repository is for the development of bioacoustic analytical tools for both humans (citizen/scientists) and machines (algorithms) to process Orcasound data -- either post-processing of archived raw FLAC files or real-time analysis of the lossy stream and/or FLAC files. The long-term goals are to characterize underwater noise in real-time and promote a friendly competition between humans and machines that leads to synergistic real-time, cloud-based processing of bioacoustic data.

How to access Orcasound acoustic data

Each node of the Orcasound hydrophone network streams audio data to AWS S3 data buckets, all of which are open-access. If you would like to access data, read the access.md file.

Resources:

• Orcasound orcadata wiki - updated activity & resources maintained by the community
• Data for Good tarball of sound samples

Resources to develop:

Archive of signals, noise, and empirical data for machine learning and teaching human listeners

• Example of Orcasound FLAC files (48, 96, 192 kHz)
• Guidance on how to access S3 buckets (CLI and/or Cloud9)
  • AWS CLI set-up and syntax -- access public Orcasound S3 buckets

Experiments in cloud-based bio/acoustic analysis

• AWS EC2 - Val set up scripts to upload AIS data from Orcasound Lab and build ship data set in RDS ** Lamba - Erika considered using it to deploy her ML model ** Cloud9 IDE ** Batch ** ECS
• Azure ** Pod.Cast pulls archived data to a Blob for labeling app

Other related open-source projects, and tools for testing tools (e.g. algorithms) with Orcasound data

• Demonstrate how to run a Pamguard module on Orcasound data (archived first; then real-time)
• Ishmael?
• Triton?