Abstract:
The use of feed-forward artificial neural network to categorize a selected set of Sri Lankan bird
species based on their vocalization is presented. The inputs to the neural network were
frequencies of bird vocalizations where each vocalization was characterized by a frequency
range. Out of the selected birds, only two birds showed peak frequency values below 1,000 Hz.
The Sri Lanka Scaly Thrush has the maximum average peak frequency of 7,761 Hz and the
Green Billed Coucal has the lowest of 334 Hz. The preliminary results show that the artificial
neural network which was trained to classify individual birds based on their frequency features
had an accuracy of greater than 90% for several bird types
