Applying neural network on the content-based audio classification

Many audio and multimedia applications would benefit if they could interpret the content of audio rather than relying on descriptions or keywords. These applications include multimedia databases and file systems, digital libraries, automatic segmentation or indexing of video (e.g., news or sports storage), and surveillance. This paper describes a novel content-based audio classification approach based on neural network and genetic algorithm. Experiments show this approach achieves a good performance of the classification.