Reordering Features with Weights Fusion in Multiclass and Multiple-Kernel Speech Emotion Recognition
The selection of feature subset is a crucial aspect in speech emotion recognition problem. In this paper, a Reordering Features with Weights Fusion (RFWF) algorithm is proposed for selecting more effective and compact feature subset. The RFWF algorithm fuses the weights reflecting the relevance, com...
Main Authors: | Xiaoqing Jiang, Kewen Xia, Lingyin Wang, Yongliang Lin |
---|---|
Format: | Article |
Language: | English |
Published: |
Hindawi Limited
2017-01-01
|
Series: | Journal of Electrical and Computer Engineering |
Online Access: | http://dx.doi.org/10.1155/2017/8709518 |
Similar Items
-
Scalable Reordering Models for SMT based on Multiclass SVM
by: Alrajeh Abdullah, et al.
Published: (2015-04-01) -
Scalable reordering models for SMT based on multiclass SVM
by: Alrajeh, Abdullah, et al.
Published: (2015) -
Weighted Feature Gaussian Kernel SVM for Emotion Recognition
by: Wei Wei, et al.
Published: (2016-01-01) -
SELFIE SIGN LANGUAGE RECOGNITION WITH MULTIPLE FEATURES ON ADABOOST MULTILABEL MULTICLASS CLASSIFIER
by: G. ANANTHA RAO, et al.
Published: (2018-08-01) -
Exploration of Complementary Features for Speech Emotion Recognition Based on Kernel Extreme Learning Machine
by: Lili Guo, et al.
Published: (2019-01-01)