I wanted to do something similar to this, then I started doing some research on birds in general, and those in my locality, then I started learning about Audio and spectograms and Nyquist Theorem and many other interesting audio stuff.
Then I started going through the Intro to Conservation Bioacoustics by Cornell course, and started watching Bioacoustic Talks by the K. Lisa Yang Center cornell center.
And now I am almost at the point where I cant start manually tagging audio sets, for target species so that I can train custom classifiers to identify birds in Rwanda which are poorly detected by birdnet.
TLDR: Being jobless can lead you into interesting ventures.
Thanks for sharing these resources and your story! I followed a very similar path, and ended up doing a biodiversity related MSc, with my dissertation being a custom classifier for poorly detected species in Príncipe. BirdNET and Perch are phenomenal achievements, but struggle in regions where, ironically, most of the world’s biodiversity is. What you’re doing for Rwandan species is so important!!
Then I started going through the Intro to Conservation Bioacoustics by Cornell course, and started watching Bioacoustic Talks by the K. Lisa Yang Center cornell center.
And now I am almost at the point where I cant start manually tagging audio sets, for target species so that I can train custom classifiers to identify birds in Rwanda which are poorly detected by birdnet.
TLDR: Being jobless can lead you into interesting ventures.
* Nyquist Theorem. https://www.youtube.com/watch?v=IZJQXlbm2dU
* Intro to Conservation Bioacoustics https://www.birds.cornell.edu/ccb/pam-materials
* Bioacoustic Talks https://www.youtube.com/@CornellSounds
There's also an excellent alternative to BirdNet-Pi that runs well on non-Raspberry-Pi machines: https://github.com/tphakala/birdnet-go