Design of BP Speaker Recognition System Based on KPCA-MFCC Parameter Optimization
Authors
Fengjuan Miao, Tongri Sun, Bairui Tao, Kaida Liu, Ding Liu, Xiaoxu Lu
Corresponding Author
Fengjuan Miao
Available Online May 2018.
- DOI
- 10.2991/meees-18.2018.34How to use a DOI?
- Keywords
- KPCA, MFCC, BP, Speaker Recognition.
- Abstract
The recognition of the speaker through machine learning algorithm has become a hot spot of research. On the basis of speaker recognition based on BP and traditional MFCC characteristic parameters, the feature parameters of MFCC are reduced by KPCA algorithm, and the BP neural network algorithm is used as the back-end recognition model to classify the speaker. The improved algorithm is simulated on the MATLAB platform and compared with the traditional PCA algorithm. The experimental results show that the improved algorithm has a great improvement in recognition efficiency and recognition accuracy and has a good research value.
- Copyright
- © 2018, 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 - Fengjuan Miao AU - Tongri Sun AU - Bairui Tao AU - Kaida Liu AU - Ding Liu AU - Xiaoxu Lu PY - 2018/05 DA - 2018/05 TI - Design of BP Speaker Recognition System Based on KPCA-MFCC Parameter Optimization BT - Proceedings of the 2018 International Conference on Mechanical, Electrical, Electronic Engineering & Science (MEEES 2018) PB - Atlantis Press SP - 187 EP - 190 SN - 2352-5401 UR - https://doi.org/10.2991/meees-18.2018.34 DO - 10.2991/meees-18.2018.34 ID - Miao2018/05 ER -