| Autor: |
Garcia Arnal Barbedo, Jayme, Lopes, Amauri |
| Předmět: |
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| Zdroj: |
AES Journal of the Audio Engineering Society: Audio, Acoustics, Applications; Jul/Aug2006, Vol. 54 Issue 7/8, p571-588, 18p, 4 Diagrams, 6 Charts, 5 Graphs |
| Abstrakt: |
A New method for discriminating between speech and music signals is introduced. The strategy is based on the extraction of four features, whose values are combined linearly into a unique parameter. This parameter is used to distinguish between the two kinds of signals. The method has achieved an accuracy superior to 99%, even for severely degraded and noisy signals. Moreover, the low dimensionality of the feature space, together with a very simple information-merging technique, has resulted in a remarkable robustness to new situations. The low computational complexity of the method makes it appropriate for applications that demand real-time operation. Finally excellent resolution for the segmentation of audio streams is achieved by manipulating the analyzed data properly. [ABSTRACT FROM AUTHOR] |
| Databáze: |
Supplemental Index |
| Externí odkaz: |
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