MATEC Web of Conferences
Volume 35, 20152015 4th International Conference on Mechanics and Control Engineering (ICMCE 2015)
|Number of page(s)||4|
|Section||Computer theory and application|
|Published online||16 December 2015|
An Optimization Method for Support Vector Machine Applied to Speech Emotion Recognition
1 Department of Electrical Information and Engineering, Changchun University, China
2 Department of Information Engineering, Changchun University of Finance and Economics, China
a Corresponding author: email@example.com
On the basis of the analysis of support vector machine model, an improved MFCC feature parameters have been adopted. Support vector machine has been used as identification model of speech emotion recognition system. For classification problems of support vector machine, an algorithm of optimization parameters has been presented. The algorithm improves the speed of solving and accuracy, and has a good classification results. Experimental results show that, in different environment, the parameter optimization method increases the recognition rate, reduces training time and has good robustness compared to traditional methods.
© Owned by the authors, published by EDP Sciences, 2015
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
Current usage metrics show cumulative count of Article Views (full-text article views including HTML views, PDF and ePub downloads, according to the available data) and Abstracts Views on Vision4Press platform.
Data correspond to usage on the plateform after 2015. The current usage metrics is available 48-96 hours after online publication and is updated daily on week days.
Initial download of the metrics may take a while.