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Audio Classification Based on MPEG-7 Spectral Basis Representations
Citation key 0795Kim2004
Author Hyoung-Gook Kim and Nicolas Moreau and Thomas Sikora
Pages 16–725
Year 2004
Journal IEEE Transactions on Circuits and Systems for Video Technology 7, Special Issue on Audio and Video Analysis for Multimedia Interactive Services
Volume 14
Number 5
Month may
Abstract classification and retrieval technique targeted for analysis of film material. The technique consists of low-level descriptors and high-level description schemes. For low-level descriptors, low-dimensional features such as audio spectrum projection based on audio spectrum basis descriptors is produced in order to find a balanced tradeoff between reducing dimensionality and retaining maximum information content. High-level description schemes are used to describe the modeling of reduced-dimension features, the procedure of audio classification, and retrieval. A classifier based on continuous hidden Markov models is applied. The sound model state path, which is selected according to the maximum-likelihood model, is stored in an MPEG-7 sound database and used as an index for query applications. Various experiments are presented where the speaker- and sound-recognition rates are compared for different feature extraction methods. Using independent ccomponent analysis, we achieved better results than normalized audio spectrum envelope and principal component analysis in a speaker recognition system. In audio classification experiments, audio sounds are classified into selected sound classes in real time with an accuracy of 96%.
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