Linearized distortion model for robust speech recognition in noisy environments - HE Yong-jun1; HAN Ji-qing1 (Tongxin xuebao)
The robustness of speech recognition system in noisy environments was investigated.The distortion model in Mel-frequency cepstral coefficient（MFCC） domain is highly non-linear and difficult to deal with.A new linear distortion model was proposed by replacing the logarithm operation with its piecewise linear interpolation function.Then the esti-mation of noise parameters and compensation of acoustic models were provided.The proposed method can avoid model error introduced by utilizing linearization methods based on vector Taylor series（VTS） expansion,and significantly im-prove the robustness of recognizer in noisy environments.