Design of BP Speaker Recognition System Based on KPCA-MFCC Parameter Optimization

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/).

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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  -