For the conservation of avian biodiversity, bird detection is vital since it allows ornithologists
to quantify which species exist in a particular area. Analyzing their acoustic signals enables
the efficient identification of multiple bird species from overlapping recordings. This paper
addresses classifying bird vocalizations in real-time audio recording using acoustic analysis.
Schemes based on recurrent neural networks (RNN) are presented in the proposed work.
Gated-recurrent units (GRU) are a particular type of RNN that has shown remarkable …