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Abstract
This paper presents a novel method to recognize inharmonic and transient bird sounds efficiently. The recognition algorithm consists of feature extraction using wavelet decomposition and recognition using either supervised or unsupervised classifier. The proposed method was tested on sounds of eight bird species of which five species have inharmonic sounds and three reference species have harmonic sounds. Inharmonic sounds are not well matched to the conventional spectral analysis methods, because the spectral domain does not include any visible trajectories that computer can track and identify. Thus, the wavelet analysis was selected due to its ability to preserve both frequency and temporal information, and its ability to analyze signals which contain discontinuities and sharp spikes. The shift invariant feature vectors calculated from the wavelet coefficients were used as inputs of two neural networks: the unsupervised self-organizing map (SOM) and the supervised multilayer perceptron (MLP). The results were encouraging: the SOM network recognized 78% and the MLP network 96% of the test sounds correctly.
Highlights
Most birds make different kinds of sounds which are used in communication with other conspecifics and between different species
All the sounds were decomposed into the wavelet coefficients using the wavelet packet decomposition (WPD)
The areas marked with letters present how sounds of each bird species were situated in the 10 × 10 self-organizing map (SOM) network
Summary
Most birds make different kinds of sounds which are used in communication with other conspecifics and between different species. Bird sounds can be tonal or inharmonic, which is one way to divide the bird species into groups. Inharmonic sounds are often transient and their frequency contents are very near each other. Bird vocalization contains both songs and calls. Calls are shorter and simpler than songs, and both sexes produce them throughout the year. It seems that most birds have from 5 to 15 distinct calls, and the functions of them can be, for example, flight, alarm, excitement, and so on. In many species there is high individual and regional variability in phrases and song patterns [6,7,8,9]. One is the variation of different sound types and another is the variation across geographic regions and among individuals
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