We present an approach to content-based sound retrieval using auditory models, self-organizing neural networks, and string matching techniques. It addresses the issues of spotting perceptually similar occurrences of aparticular sound event in an audio document. After introducing the problem and the basic approach we describe the individual stages of the system and give references to additional literature. The third section of the paper summarizes the preliminary experiments involving auditory models and self-organizing maps we carried out so far, and the final discussion reflects on the overall concept and suggests further directions.
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