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 to promote a friendly collaboration among humans and machines that leads to synergistic real-time, cloud-based processing of bioacoustic 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.
- Orcasound orcadata wiki - updated activity & resources maintained by the community
- Data for Good tarball of sound samples
An open access 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
- AWS EC2 - Val set up scripts to upload AIS data from Orcasound Lab and build ship data set in RDS ** Lambda - 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?