Recognition of practical English speech emotion using improved Quantum Ant Colony Algorithm
Authors
Lihui Du, Yueguang Li
Corresponding Author
Lihui Du
Available Online January 2015.
- DOI
- 10.2991/isci-15.2015.287How to use a DOI?
- Keywords
- improved Quantum Ant Colony Algorithm; English speech emotion; Recognition; heuristics
- Abstract
Due to the drawbacks in Support Vector Machine (SVM) parameter optimization, an improved quantum ant colony algorithm was proposed, and the learning ability in practical English speech emotion recognition was improved. The experimental results showed that quantum ant colony algorithm may significantly improve the practical English speech emotion recognition.
- Copyright
- © 2015, the Authors. Published by Atlantis Press.
- Open Access
- This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).
Cite this article
TY - CONF AU - Lihui Du AU - Yueguang Li PY - 2015/01 DA - 2015/01 TI - Recognition of practical English speech emotion using improved Quantum Ant Colony Algorithm BT - Proceedings of the 2015 International Symposium on Computers & Informatics PB - Atlantis Press SP - 2192 EP - 2199 SN - 2352-538X UR - https://doi.org/10.2991/isci-15.2015.287 DO - 10.2991/isci-15.2015.287 ID - Du2015/01 ER -