Abstract: The effects of amplitude modulation (AM) cues on human musical instrument recognition were investigated.An automatic musical instrument recognition experiment was carried out.The following stages were manipulated:calculation of the statistical features from AM of the musical signals extracted based on the auditory model;a support vector machine with pairwise classification strategy was used as the classifier.Totally five band conditions (2,4,8,16 and 32) and four AM extraction methods were evaluated.Results showed that recognition performance improved with the increasing of the band number,and 16 bands were sufficient for reaching asymptotic performance.The AM extraction methods also had significant effects on the performance.The analytic signal based method showed better performance than the rectification-low-pass-filter methods.The automatic recognition system showed better performance than human subjects using similar AM information.The automatic recognition system provided a computational model for predicting the performance of musical instrument recognition with cochlear implants and vocoder simulations and can be used as a reference in relevant experiments and training about musical instrument recognition with cochlear implants.