This might be difficult for a variety of reasons.
- Insects are an incredibly diverse group. Obviously, not all insects make distinct sounds, but we are still talking about far more species than birds or bats.
- Recognizers struggle with simple sounds and with sounds that are very similar to the sounds of other species. Both of these issues would be prevalent among insects. This is also why Merlin is better at identifying bird song than it is with “chip” calls.
- Recognizers are only as good as your ability to train them.
- Insect sounds are influenced by external factors. For example, many Orthopterans change the speed and/or pitch of their sounds based on the temperature, to the point that even human identifiers need to know the temperature at the time of recording to make an ID.
Many things have to happen first before this is possible, even for more recognizable groups. Audio recognition often uses similar models as image recognition, where the computer is trained on spectrogram images of the audio rather than “hearing” the audio. So the first step would be to have iNat generate a standardized spectrogram (proposed here; discussion of logistical hurtles can be read about in that thread). Then some form of moving-window recognizer has to be made because it doesn’t really work to have the computer look at the entire audio clip (it needs to take it segment by overlapping segment).