Acoustic transient classification of passive sonar signals by using vector quantization

The automatic classifications of ice-generated transient signals is examined. The classification method is a modified version of one previously used to classify speech sounds and is based on vector quantization. It uses a clustering algorithm on training data to design a signal-specific classification codebook (a set of reference spectra) for each signal type, and it compares an unknown signal event with each of the classification codebooks to make a classification decision. On a test set consisting 7 types of ice-generated signals, a recognition accuracy of 71% was achieved. Details of the experimental conditions and results are given, and recommendations for improving the performance are provided