Neuro-Fuzzy Fusion: A New Approach to Multiple Classifier System

2006 ◽  
Author(s):  
Saroj K. Meher ◽  
Ashish Ghosh ◽  
B. Uma Shankar ◽  
Lorenzo Bruzzone
Keyword(s):  
Multiple Classifier System ◽  
New Approach ◽  
Classifier System ◽  
Neuro Fuzzy ◽  
Multiple Classifier ◽  
Fuzzy Fusion

Neuro-fuzzy-combiner: an effective multiple classifier system

2010 ◽  
Vol 2 (2) ◽  
pp. 107 ◽  
Author(s):  
Ashish Ghosh ◽  
B. Uma Shankar ◽  
Lorenzo Bruzzone ◽  
Saroj K. Meher
Keyword(s):  
Multiple Classifier System ◽  
Classifier System ◽  
Neuro Fuzzy ◽  
Multiple Classifier

scholarly journals A Research of Speech Emotion Recognition Based on Deep Belief Network and SVM

2014 ◽  
Vol 2014 ◽  
pp. 1-7 ◽  
Author(s):  
Chenchen Huang ◽  
Wei Gong ◽  
Wenlong Fu ◽  
Dongyu Feng
Keyword(s):  
Feature Extraction ◽  
Emotion Recognition ◽  
Recognition Rate ◽  
Original Method ◽  
Speech Emotion Recognition ◽  
High Dimensional ◽  
Svm Classifier ◽  
Multiple Classifier System ◽  
Classifier System ◽  
Multiple Classifier

Feature extraction is a very important part in speech emotion recognition, and in allusion to feature extraction in speech emotion recognition problems, this paper proposed a new method of feature extraction, using DBNs in DNN to extract emotional features in speech signal automatically. By training a 5 layers depth DBNs, to extract speech emotion feature and incorporate multiple consecutive frames to form a high dimensional feature. The features after training in DBNs were the input of nonlinear SVM classifier, and finally speech emotion recognition multiple classifier system was achieved. The speech emotion recognition rate of the system reached 86.5%, which was 7% higher than the original method.

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