Electronic voice disguise refers to hiding the identity of a speaker by voice changing equipment or voice processing software. The restoration of disguised voice refers to changing it back to its original version， which is of great significance for speaker identification. This paper first models the restoration of disguised voices as the estimation of disguising factors in both frequency and time domains. The estimation of disguising factor is made by automatic speaker verification using i-vector. Symmetric transformation is proposed to improve the performance on parameter estimation. By virtue of the noise robustness of i-vector， the proposed method improves the estimation accuracy of the disguising factor in the real noise-containing scene， thereby improving noise robust restoration effect of electronic disguised voice. Evaluation results on noisy speech library VoxCeleb1 of the trained model on clean speech library TIMIT demonstrated good performance of the approach by reducing the error rate from 9.19% to 4.49%. The quality of the restored voice is also improved in the aspects of automatic speaker verification and auditory perception.