/“However, it turns out that the 'soundscape problem' where the microphone is just attached to a tree is a bit more difficult than identifying foreground birds

/“However, it turns out that the 'soundscape problem' where the microphone is just attached to a tree is a bit more difficult than identifying foreground birds only, using a device that can be pointed in the relevant direction by the user.“/ Yes pointing a directional mic introduces a whole new set of mechanical challenges. Maybe you could build an irregular grid of omnidirectional microphones and use signal processing to direct the beam digitally (similar to radio beam-forming). Now you’ll need more processing horsepower to do FFTs to do phase shifts. Although if you assume the bird calls only occupy discrete frequencies you might be able to save some computation by just computing those. Perhaps a machine learning model could be trained that does all of this for you. Then you get the benefit of hardware acceleration. Some ML chips can handle DSP tasks.