Bird identification is an enjoyable exercise that ties us to the natural world. The automated identification of bird species is critical in many ecological and biodiversity investigations. Birds are highly diverse, with many different sizes, shapes, colours, and habits using deep learning to identify bird species based on audio recordings. To achieve this purpose, this intends to employ the most recent Artificial Neural Networks (ANN) model. The suggested method consists of three major steps: audio data collection and preprocessing, feature extraction, and neural network classification. For studying and detecting bioacoustics signals, an ANN classification algorithm is used. The multilayer perceptron (MLP) is utilized as a classification model. The MLP takes as input a set of specified attributes and generates a unique output. The training procedure involves repeatedly sending known sounds and then iteratively modifying the weighting of the network. This aims to reduce the error between supplied and expected results.