TY - JOUR AU - Kos, Marko AU - Grašič, Matej AU - Kačič, Zdravko PY - 2009 DA - 2009/10/22 TI - Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy JO - EURASIP Journal on Advances in Signal Processing SP - 628570 VL - 2009 IS - 1 AB - This paper presents a novel feature for online speech/music segmentation based on the variance mean of filter bank energy (VMFBE). The idea that encouraged the feature's construction is energy variation in a narrow frequency sub-band. The energy varies more rapidly, and to a greater extent for speech than for music. Therefore, an energy variance in such a sub-band is greater for speech than for music. The radio broadcast database and the BNSI broadcast news database were used for feature discrimination and segmentation ability evaluation. The calculation procedure of the VMFBE feature has 4 out of 6 steps in common with the MFCC feature calculation procedure. Therefore, it is a very convenient speech/music discriminator for use in real-time automatic speech recognition systems based on MFCC features, because valuable processing time can be saved, and computation load is only slightly increased. Analysis of the feature's speech/music discriminative ability shows an average error rate below 10% for radio broadcast material and it outperforms other features used for comparison, by more than 8%. The proposed feature as a stand-alone speech/music discriminator in a segmentation system achieves an overall accuracy of over 94% on radio broadcast material. SN - 1687-6180 UR - https://doi.org/10.1155/2009/628570 DO - 10.1155/2009/628570 ID - Kos2009 ER -