title: [Speaker identification based on Mel frequency cepstrum coefficient and complexity measure].
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.
authors.affiliation: College of Biomedical Engineering and Instrument Science, Zhejiang University, Hangzhou 310027, China. maodawei@163.com
authors.forename: Dawei
authors.initials: D
authors.lastname: Mao
authors.forename: Hua
authors.initials: H
authors.lastname: Cao
authors.forename: Hamit
authors.initials: H
authors.lastname: Murat
authors.forename: Qinye
authors.initials: Q
authors.lastname: Tong
mesh_terms: D000465:Algorithms; D001185:Artificial Intelligence; D005260:Female; D006801:Humans; D008297:Male; D017711:Nonlinear Dynamics; D010363:Pattern Recognition, Automated / Q000379:methods*; D012815:Signal Processing, Computer-Assisted; D014831:Voice