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A transfer learning framework for predicting the emotional content of generalized sound events
2017
Journal of the Acoustical Society of America
Predicting the emotions evoked by generalized sound events is a relatively recent research domain which still needs attention. In this work a framework aiming to reveal potential similarities existing during the perception of emotions evoked by sound events and songs is presented. To this end the following are proposed: (a) the usage of temporal modulation features, (b) a transfer learning module based on an echo state network, and (c) a k-medoids clustering algorithm predicting valence and
doi:10.1121/1.4977749
pmid:28372068
fatcat:vwwyutbidngvtmr4mf4zzuqvha