声码器清浊音判决算法优化  

Improvement of voiced-unvoiced classification in vocoders

作　　者：党晓妍[1] 魏旋[1] 崔慧娟[1] 唐昆[1] 

机构地区：[1]清华大学电子工程系,微波与数字通信技术国家重点实验室,北京100084

出　　处：《清华大学学报（自然科学版）》2008年第7期1119-1122,共4页Journal of Tsinghua University(Science and Technology)

基　　金：国家自然科学基金资助项目(60572081)

摘　　要：为了解决低速声码器合成语音的偶发性嘶哑或变调问题,对参数提取进行改善,采用有监督学习的Fisher判决法,利用多个特征值组成的特征向量为判据;基音周期平滑的准确度在利用了更准确的清浊音信息后大有提高。测试结果表明:该算法能够大大降低清浊音误判率,减少严重基音周期错误数;应用该算法的SELP(sinuous excitationlinear prediction)2.4 kb/s的PESQ-MOS分优于2.4 kb/s的MELPe(mixed excitation linear prediction)和AMBE+(advanced multi-band excitation)算法,DRT(diagnosticrhythm test)分数达95%,具有良好的可懂度和自然度。Many kinds of 2. 4 kb/s low bit rate vocoders have occasionally hoarseness or out-of-tone speech. Hence voiced-unvoiced classification method is improved using several parameters based on Fisher method. The pitch track precision is then improved by more precise voiced-unvoiced information. Tests results show that the Fisher classification method greatly reduces the voiced-unvoiced classification error rate and number of severe half or double pitch errors. The improved 2.4 kb/s SELP （sinuous excitation linear prediction） vocoder then get a higher PESQ- MOS score, even outperforming the US government＇s MELPe and DVSI＇s AMBE ＋ algorithm at the same rate. Additionally, the improved 2. 4 kb/s SELP vocoder has diagnostic rhythm test （DRT） scores of up to 95%, which produces excellent natural and intelligible speech.

关 键 词：语音编码 清浊音判决 MELPe算法 AMBE+算法 

分 类 号：TN912.32[电子电信—通信与信息系统]