Channel and noise normalization using affine transformed cepstrum

The paper addresses the environmental mismatch problem that arises from noise and channel variabilities. A new feature mapping technique based on an optimal affine 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 affine transformation. By taking an inverse transformation, one can easily decouple from the speech the effects of the channel and noise. Alternatively, one can take a forward transform of the training data to simulate the operating conditions.