| Conference/Proceedings | 25th International AES Conference Metadata for Audio |
| Start date | 17.06.2004 |
| End date | 19.06.2004 |
| Address | London, UK |
| Author(s) | Hyoung-Gook Kim, Juan José Burred, Thomas Sikora |
| Title | How efficient is MPEG-7 for General Sound Recognition? |
| Abstract | 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. |
| File | 0780Kim2004.pdf |