Species recognition using audio processing algorithm

Small of the smallest living creature is the part of the whole ecosystem. Monitoring and maintaining this environmental health has become a task of prime importance, since human activity and climate change has placed the greater pressure on biodiversity. This helps in monitoring dangerous situations to planes caused by birds near airports and also in saving endangered species. Powerful audio signal processing techniques makes it possible to introduce automated methods for the detection of such vocalizations. The complete identification procedure essentially involves collection of recorded vocalizations of different species, audio pre-processing to remove the noise and silence, segmentation to select the most representative characterizing elements of the signal called syllable, extraction of different features commonly found in sound classification and speech recognition to obtain relevant characteristics, and decision procedures for identification, where Machine Learning (ML) algorithms are used to train employed classifiers using labelled database of previously known species of interest. Linear Discriminant Analysis (LDA) with probabilistic approach is used for recognition of bird species. The required class probabilities are obtained from linear scores function.