Cochlear implant signal processing algorithm based on frequency modulation  

作　　者：YANG Lin ZHANG Jianping WANG Di YAN Yonghong 

机构地区：[1]ThinkIT Lab.,Institute of Acoustics,Chinese Academy of Sciences Beijing 100190 [2]Institute of Physics,Chinese Academy of Sciences Beijing 100190

出　　处：《Chinese Journal of Acoustics》2010年第3期298-307,共10页声学学报（英文版）

基　　金：supported by the MOST(973 program 2004CB318106);the National Natural Science Foundation of China(10574140,60535030);the National High Technology Research and Development Program of China(863 program,2006AA010102,2006AA01Z195)

摘　　要：A strategy was proposed to improve the performance of continuous interleaved sampling algorithm by introducing partial temporal fine structure cues,namely frequency modulation （FM） information,into the slowly varying temporal envelops.The improved algorithm has its own application values because it does not introduce too much high-frequency components into the model,which can not be perceived by deaf patients.The psychoacoustic experimental data showed that the introduction of the frequency modulation information can improve the CI performance greatly：the intelligibility of vowel perception can get over 28%improvements, tone recognition scores can increase more than 20%at various noise conditions,and under moderate noise conditions the consonant and sentence recognition can also be improved 22.9% and 28.3%respectively.A strategy was proposed to improve the performance of continuous interleaved sampling algorithm by introducing partial temporal fine structure cues,namely frequency modulation （FM） information,into the slowly varying temporal envelops.The improved algorithm has its own application values because it does not introduce too much high-frequency components into the model,which can not be perceived by deaf patients.The psychoacoustic experimental data showed that the introduction of the frequency modulation information can improve the CI performance greatly：the intelligibility of vowel perception can get over 28%improvements, tone recognition scores can increase more than 20%at various noise conditions,and under moderate noise conditions the consonant and sentence recognition can also be improved 22.9% and 28.3%respectively.

分 类 号：TU998.12[建筑科学—市政工程] T-1[一般工业技术]