The article is very thin on actual technical details. It doesn’t describe how the spectrograms are processed or details of the neural network they’re using (oth

The article is very thin on actual technical details. It doesn’t describe how the spectrograms are processed or details of the neural network they’re using (other than using convolutions, which is pretty standard in CV/audio/speech processing). What is interesting to me, though, is that they mention the importance of more precise time labeling of sounds. Previous BirdCLEF Kaggle competitions just provided many-minute long recordings where all that is known (labelled) is that a certain list of species are to be heard, but not when in the recording. That’s not too useful as training data, as they point out in the article: This can lead to problems: if other species are singing in the same recording, the model will erroneously call all species in the recording a White-breasted Nuthatch, leading to false predictions.