Adaptive Recognition with Layered Optimization
ARLO was developed for classifying bird calls and using visualizations to help scholars classify pollen grains. ARLO has the ability to extract basic prosodic features such as pitch, rhythm and timbre for discovery (clustering) and automated classification (prediction or supervised learning), as well as visualizations. The current implementation of ARLO for modeling runs in parallel on systems at the Texas Advanced Computing Center (TACC) on the Stampede supercomputer.
ARLO is open-source, meaning you are free to use or modify it, whether for yourself or to contribute back to the community. The ARLO source code repositories are available on Bitbucket
We are always on the lookout for additional help. See Contributing for more information.
The official ARLO Wiki is available at http://wiki.arloproject.com/
Doxygen Docs auto-generated from the source code are available:
Additionally, the HiPSTAS group, an organization of users focused around ARLO and similar technologies, maintains further documentation at https://sites.google.com/site/nehhipstas/documentation
A freely hosted version is currently available for a limited number of users, though we are pretty much at capacity given our current resources. However, if you would like to contribute resources or setup your own installation, let us know and we'll see how we can help.