MATEC Web of Conferences
Volume 61, 2016The International Seminar on Applied Physics, Optoelectronics and Photonics (APOP 2016)
|Number of page(s)||4|
|Section||Chapter 3 Information Security and Computer Science|
|Published online||28 June 2016|
Feature Fusion Algorithm for Multimodal Emotion Recognition from Speech and Facial Expression Signal
Bohai University, China
a Corresponding author: email@example.com
In order to overcome the limitation of single mode emotion recognition. This paper describes a novel multimodal emotion recognition algorithm, and takes speech signal and facial expression signal as the research subjects. First, fuse the speech signal feature and facial expression signal feature, get sample sets by putting back sampling, and then get classifiers by BP neural network (BPNN). Second, measure the difference between two classifiers by double error difference selection strategy. Finally, get the final recognition result by the majority voting rule. Experiments show the method improves the accuracy of emotion recognition by giving full play to the advantages of decision level fusion and feature level fusion, and makes the whole fusion process close to human emotion recognition more, with a recognition rate 90.4%.
© Owned by the authors, published by EDP Sciences, 2016
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.
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