Đang chuẩn bị nút TẢI XUỐNG, xin hãy chờ
Tải xuống
Research Article Online Speech/Music Segmentation Based on the Variance Mean of Filter Bank Energy | Hindawi Publishing Corporation EURASIP Journal on Advances in Signal Processing Volume 2009 Article ID 628570 13 pages doi 10.1155 2009 628570 Research Article Online Speech Music Segmentation Based on the Variance Mean of Filter Bank Energy Marko Kos Matej Graăic and Zdravko KaCiC Faculty of Electrical Engineering and Computer Science University of Maribor Smetanova ul. 17 2000 Maribor Slovenia Correspondence should be addressed to Marko Kos marko.kos@uni-mb.si Received 6 March 2009 Revised 4 June 2009 Accepted 2 September 2009 Recommended by Aggelos Pikrakis 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 standalone speech music discriminator in a segmentation system achieves an overall accuracy of over 94 on radio broadcast material. Copyright 2009 Marko Kos et al. This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use distribution and .