Speaker identification based on Mel frequency cepstrum coefficient and complexity measure.
- Author:
Dawei MAO
1
;
Hua CAO
;
Hamit MURAT
;
Qinye TONG
Author Information
1. College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China. maodawei@163.com
- Publication Type:Journal Article
- MeSH:
Algorithms;
Artificial Intelligence;
Female;
Humans;
Male;
Nonlinear Dynamics;
Pattern Recognition, Automated;
methods;
Signal Processing, Computer-Assisted;
Voice
- From:
Journal of Biomedical Engineering
2006;23(4):882-886
- CountryChina
- Language:Chinese
-
Abstract:
In present, the most basically used parameters for speaker identification are linear predictive coding (LPC) parameter, Mel frequency cepstrum coefficient(MFCC), etc. First in this paper only MFCC was used as the parameter and then Lempel-Ziv Complexity was combined with MFCC as parameters. The text-dependent recognition rate of 50 speakers increased from 42% to 80% and the text-independent recognition rate of 50 speakers increased from 60% to 72%. This test shows that Lempel-Ziv complexity, as a new parameter, can be applied to speaker identification.
