Titlebook: Algorithms in Ambient Intelligence; Wim F. J. Verhaegh,Emile Aarts,Jan Korst Book 2004 Springer Science+Business Media Dordrecht 2004 Audi

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Features for Audio Classificationndard Gaussian framework for classification, results show that the temporal behavior of features is important for automatic audio classification. In addition, classification is better, on average, if based on features from models of auditory perception rather than on standard features.

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From Stereotypes to Personal Profiles Via Viewer Feedbackh a different set of stereotypes applied to all the users. The best performance is in the range of 11% error. This performance compares favorably with the best we have got to date on recommenders trained on user-specific data.

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