Unvoiced Chinese Digital Recognition Based On Facial Myoelectric Signal

摘要：

Different from multi-channel MES, eleven Chinese digitals zero to ten (/i/, /er/, /san/, /si/, /wu/, /liu/, /qi/, /ba/, /jiu/, and /shi/) are studied based on the one-channel detected myoelectric signal (MES). Zygomaticus major and anterior belly of the digastric are carefully selected as the electrodes site of MES detected. According to MES characteristic, wavelet transform coefficients, AR model coefficients and real cepstral coefficients are calculated as the features of MES. Using GA (Genetic Arithmetic) sixteen features are selected from the original features as the inputs of SVM (Support Vector Machine) classifier. The result shows that using the MES to recognise unvoiced speech is a promising way.

作者: Xueqin Jia Xu Wang Jinghong Li Dan Yang Yue Song

作者单位: School of information science and engineering Northeastern University Shenyang, Liaoning, China

会议类型: 国际会议

会议名称: 2006 International Conference on Communications,Circuits and Systems(第四届国际通信、电路与系统学术会议)

会议地点: 广西桂林

会议语种:英文

页码: 598-601

在线出版日期: 2006-06-25（万方平台首次上网日期，不代表论文的发表时间）