Fractal dimension analysis of audio signals for Indian musical instrument recognition

The application of fractal geometry to musical signals and instrumental recognition system is not been widely experimented. The fractal dimension D is a very important characteristic of fractals useful for segmentation. This paper introduces an instrument identification system, which uses fractal dimension for segmentation of audio signals. This research is organized in three parts. The first part of this research investigates fractal dimension based segmentation of musical sounds for feature extraction and recognition. The second part explores extraction of the feature set from the segmented musical signal. The feature set of the proposed system includes spectral, perceptual and temporal features of the musical signal. Third part of this research describes about the neural network classifiers. The system has been experimented with kNN classifier and multi-layer perceptron classifier and the performance of these were compared. The proposed system has been trained and tested with 10 different Indian musical instruments sound samples. The sample set contains solo and duet recordings. The system has shown overall recognition rate of 89.7% for solo and 82.8 % for duet.