In case anyone is interested, I'm developing a Python/Tensorflow-based open source project, vak, that annotates birdsong, similar to what Deepsqueak does: https

In case anyone is interested, I'm developing a Python/Tensorflow-based open source project, vak, that annotates birdsong, similar to what Deepsqueak does: https://github.com/NickleDave/vak https://github.com/NickleDave/vak (DeepSqueak runs in Matlab.) We've also developed a neural net architecture which we find gives low error across individuals and is much more lightweight than Faster-RCNN, the net that Deepsqueak uses under the hood: https://github.com/yardencsGitHub/tweetynet/ https://github.com/yardencsGitHub/tweetynet/ I've tried to make it so that any net (even Faster-RCNN) can be used with vak and I've built tools so it works with multiple audio and annotation formats (https://github.com/NickleDave/crowsetta https://github.com/NickleDave/crowsetta). We're finally about to submit a paper on this, thought I'd share here now case anyone is interested in contributing to the library in the future. (edit for clarity)