Improvement of voiced-unvoiced classification in vocoders

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.