I am using BirdNET in projects to assess breeding bird acoustic phenology. BirdNET has provided a compelling opportunity to transition away from acoustic indices (which, though useful, provide challenges for easy interpretation) and toward characterizing species-based activity levels instead.
One of the challenges (and opportunities) of BirdNET is that it gives a confidence score output for the species of interest, but it does not classify the detection as a song or call. In avian species, songs and calls are largely believed to have different functions. The song/call issue also presents challenges in verification, particularly if a verifier knows the song well but is less familiar with the various call types a bird may have (I've worked on developing a flexible / generalizable solution to this problem here, but it's not perfect).
In my project, I would prefer to focus more on songs, and am having trouble figuring out how to deal with the songs vs. calls BirdNET detects. I suppose one solution could be to build an additional classifier on top of BirdNET that classifies further into a song or call, and another might be to estimate song vs. call rates throughout the breeding season based on a verified subsample.
How have others dealt with this?