基于多项式拟合的中性-情感模型转换算法  

Neutral-emotion model transformation algorithm based on polynomial function fitting.

作　　者：单振宇[1] 杨莹春[1] 

机构地区：[1]浙江大学计算机科学与技术学院,杭州310027

出　　处：《计算机工程与应用》2008年第21期206-208,221,共4页Computer Engineering and Applications

基　　金：国家高技术研究发展计划( 863)( the National High-Tech Research and Development Plan of China under Grant No.2006AA01Z136);浙江省自然科学基金(the Natural Science Foundation of Zhejiang Province of China under Grant No.Y106705)

摘　　要：情绪变化问题是说话人识别技术面临的一个难题。为了解决该问题,提出了基于多项式方程拟合的中性-情感模型转换算法。该算法建立了中性模型和情感模型之间的函数关系,只需要说话人的中性语音就能训练其各种情感类型的说话人模型。在普通话情感语音库上的实验表明,采用该方法后识别算法的等错误率由16.06%降低到10.31%,提高了系统性能。One of the largest challenges in speaker recognition is dealing with speaker-emotion variability problem.A neutral-emotion model transformation algorithm is presented to overcome this limitation,which builds a relationship between emotion and neutral models.In this method,only neutral speech is needed in training emotion models.The experiments on MASC show that the EER is reduced to 10.31% from the 16.06%,and the recognition performance can be improved by this algorithm.

关 键 词：说话人识别 高斯混合模型 情感语音 

分 类 号：TP391[自动化与计算机技术—计算机应用技术]