journal paper

JournalIEEE Transactions on Circuits and Systems for Video Technology 7, Special Issue on Audio and Video Analysis for Multimedia Interactive Services
DateMay 2004
Author(s)Hyoung-Gook Kim, Nicolas Moreau, Thomas Sikora
TitleAudio Classification Based on MPEG-7 Spectral Basis Representations
Abstractclassification 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%.
Key wordsAudio spectrum basis (ASB), audio spectrum projection (ASP), hidden Markov models (HMMs), independent component analysis (ICA), MPEG-7.