Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech

Classifier Subset Selection for the Stacked Generalization Method Applied to Emotion Recognition in Speech

In this paper, a new supervised classification paradigm, called classifier subset selection for stacked generalization (CSS stacking), is presented to deal with speech emotion recognition. The new approach consists of an improvement of a bi-level multi-classifier system known as stacking generalizat...

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Bibliographic Details
Main Authors: Aitor Álvarez, Basilio Sierra, Andoni Arruti, Juan-Miguel López-Gil, Nestor Garay-Vitoria
Format: Article
Language:English
Published: MDPI AG 2015-12-01
Series:Sensors
Subjects:
affective computing
machine learning
speech emotion recognition
Online Access:http://www.mdpi.com/1424-8220/16/1/21

Internet

http://www.mdpi.com/1424-8220/16/1/21

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