Recognizing Birds from Sound - The 2018 BirdCLEF Baseline System
This work addresses the need for reliable bird species recognition for researchers, conservation biologists, and birders, but it is incremental as it builds on existing neural network methods.
The paper tackles bird species identification from audio recordings by presenting a baseline system using convolutional neural networks, aimed at providing a reference for participants in the 2018 BirdCLEF challenge.
Reliable identification of bird species in recorded audio files would be a transformative tool for researchers, conservation biologists, and birders. In recent years, artificial neural networks have greatly improved the detection quality of machine learning systems for bird species recognition. We present a baseline system using convolutional neural networks. We publish our code base as reference for participants in the 2018 LifeCLEF bird identification task and discuss our experiments and potential improvements.