Articulation constrained learning with application to speech emotion recognition

Volume: 2019, Issue: 1
Published: Aug 20, 2019
Abstract
Speech emotion recognition methods combining articulatory information with acoustic features have been previously shown to improve recognition performance. Collection of articulatory data on a large scale may not be feasible in many scenarios, thus restricting the scope and applicability of such methods. In this paper, a discriminative learning method for emotion recognition using both articulatory and acoustic information is proposed. A...
Paper Details
Title
Articulation constrained learning with application to speech emotion recognition
Published Date
Aug 20, 2019
Volume
2019
Issue
1
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