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Bioacoustics play a major role in the field of ornithology, ecology, animal behaviour study, habitat monitoring, species conservation and design of deterrent system. This work focusses on the design and implementation and performance evaluation of an automatic, more efficient and flexible bird sound based recognition system for classifying eight species of popular Eurasian birds the standard online annotated databases. A dedicated virtual instrument tool with effective GUI is developed that acquires, pre-processes the sound samples and generates statistically evaluated short term Fourier transform spectrogram based feature matrix, suited for characterization of vocalization patterns of bird species. Using the well-labelled feature data of sound records, multi-layer perceptron artificial neural network (MLP-NN) classifier model is designed, trained, tested and optimized using feedforward-backpropagation supervised …