%0 Journal Article
%T Speaker Recognition Based on Time-Frequency Distribution and MFCC<br>基于时频分布与MFCC的说话人识别
%A JIN Yin-Yan
%A YU Feng-Qin
%A HE Yan
%A <br>金银燕
%A 于凤芹
%A 何艳
%J 计算机系统应用
%D 2012
%I 
%X Because MFCC can＇t reflect the dynamic characteristics of speech signal and their own non-stationary, a feature extraction method by combining time-frequency distribution with MFCC is proposed. First get time-frequency distribution of speech signal, and convert time-frequency domain into frequency domain, then extract MFCC＋MFCC as characteristic parameters. Finally speaker recognition uses the support vector machine. The simulation experiment compares recognition performance when MFCC and MFCC＋MFCC are respectively as characteristic parameters by speech signal and all kinds of time-frequency distribution. Results show that the speaker recognition performance using MFCC＋MFCC based on the CWD time-frequency distribution can be improved to 95.7%.
%K STFT
%K WVD
%K CWD
%K MFCC
%K speaker recognition<br>短时傅里叶变换
%K Wigner-Ville分布
%K Choi-Williams分布
%K Mel频率倒谱系数
%K 说话人识别
%U http://www.alljournals.cn/get_abstract_url.aspx?pcid=5B3AB970F71A803DEACDC0559115BFCF0A068CD97DD29835&cid=8240383F08CE46C8B05036380D75B607&jid=D4F6864C950C88FFCE5B6C948A639E39&aid=2F008F04A30914BA3DE6713714FCE256&yid=99E9153A83D4CB11&vid=659D3B06EBF534A7&iid=E158A972A605785F&sid=3A0155B37D8FF829&eid=982245BA1179840E&journal_id=1003-3254&journal_name=计算机系统应用&referenced_num=0&reference_num=7