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- W2364477688 abstract "MFCC and its dynamics were used to distinguish pure speech,impure speech,instrument sounds,songs,and environment sounds.Considering the characteristics of such features and differences between audio types,a hierarchical discrimination algorithm was proposed based on discriminative model training and feature filtration,which trained GMMs(Gaussian mixture models) in each layer and selected the feature subset resulting in maximal separability for them.Within about 2-hour-long database,experimental results indicate that the algorithm outperforms original 90-dimension system by 23.5% in average error rate,as well as obtains a substantial dimensionality reduction for discriminator every layer." @default.
- W2364477688 created "2016-06-24" @default.
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- W2364477688 date "2007-01-01" @default.
- W2364477688 modified "2023-09-25" @default.
- W2364477688 title "Audio classification based on GMM and feature filtration for hierarchical discriminators" @default.
- W2364477688 hasPublicationYear "2007" @default.
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