Channel and noise normalization using affine transformed cepstrum

This paper addresses the environmental mismatch problem that arises from noise and channel variabilities. A new feature mapping technique based on an optimal a ne transform of the cepstrum is proposed to solve the mismatch problem observed over the speaker recognition systems. It is designed based on the fact that both the channel and noise interferences basically cause the cepstrum space to undergo an a ne transformation. By taking an inverse transformation, we can easily decouple from the speech the e ects of the channel and noise. Alternatively, we can take a forward transform of the training data to simulate the operating conditions.