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How Efficient is MPEG-7 for General Sound Recognition?

Our challenge is to analyze/classify video sound track content for indexing purposes. To this end we compare the performance of MPEG-7 Audio Spectrum Projection (ASP) features based on several basis decomposition algorithms vs. Mel-scale Frequency Cepstrum Coefficients (MFCC). For basis decomposition in the feature extraction we evaluate three approaches: Principal Component Analysis (PCA), Independent Component Analysis (ICA), and Non-negative Matrix Factorization (NMF). Audio features are computed from these reduced vectors and are fed into a continuous hidden Markov model (CHMM) classifier. Our conclusion is that established MFCC features yield better performance compared to MPEG-7 ASP in the general sound recognition under practical constraints.

Authors: Kim, Hyoung-Gook; Sikora, Thomas
Affiliation: Communication Systems Group, Technical University of Berlin, Germany
AES Conference:25th International Conference: Metadata for Audio (June 2004)
Paper Number:5-2 Import into BibTeX
Subject:Metadata for Audio

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