Automatic classification of speech and music using neural networks

The importance of automatic discrimination between speech signals and music signals has evolved as a research topic over recent years. The need to classify audio into categories such as speech or music is an important aspect of many multimedia document retrieval systems. Several approaches have been previously used to discriminate between speech and music data. In this paper, we propose the use of the mean and variance of the discrete wavelet transform in addition to other features that have been used previously for audio classification. We have used Multi-Layer Perceptron (MLP) Neural Networks as a classifier. Our initial tests have shown encouraging results that indicate the viability of our approach.