A speech/music discriminator using RMS and zero-crossings

An audio segmentation method and a speech/music classifier are proposed. The characteristics used are considerably reduced. Segmentation is based on mean signal amplitude distribution, whereas classification utilizes an additional characteristic related to the mean frequency. The segmentation and classification algorithms were benchmarked on a large data set, with correct segmentation about 97% of the time and correct classification about 95%.