计算机技术与发展Issue(1)：39-42,47,5.DOI:10.3969/j.issn.1673-629X.2016.01.008
基于 LPC 和 MFCC 得分融合的说话人辨认
Speaker Identification Based on Score Combination of LPC and MFCC
摘要
Abstract
At present,speaker recognition technology has made great progress in clean voice. But in daily life,there are various factors, such as environmental noise and healthy condition,impacting recognition rate of speaker recognition system. The cold tends to induce the nasal cavity’s inflammation,and changes the volume and shape of the nasal cavity and then changes the vocal characteristics of the speak-er. In order to effectively use the complementarity of scores from different feature parameter,the performance’s change of speaker identi-fication system was studied when the speaker gets the cold. So the method was proposed using linear prediction coefficient and MEL ceps-trum coefficient to train the speaker model respectively,and then score normalization method is used to process scores from two feature systems. Finally,two outputs were weighted. The experimental results show that for normal speech,this method can improve the identifi-cation performance;for cold speech,the method improves the identification performance by 12. 5% when the number of Gaussian compo-nents equals to sixteen compared with the system taking MFCC as feature,by 8. 5% to the LPC system.关键词
感冒语音/说话人辨认/得分融合/得分归一化Key words
cold speech/speaker identification/score combination/score normalization分类
信息技术与安全科学引用本文复制引用
单燕燕..基于 LPC 和 MFCC 得分融合的说话人辨认[J].计算机技术与发展,2016,(1):39-42,47,5.基金项目
国家自然科学基金资助项目(61271335) （61271335）
国家重点基础研究发展计划(2011CB302303) （2011CB302303）
