Learning the influence of additive noise and channel distortions from training data is an effective approach for robust speech recognition. We had proposed a novel method of discriminative learning environmental features according to Minimum Classification Error (MCE) criterion in the previous work, in which additive noise are expressed by the weighted combination of multiple types of noises, and the channel distortions are assumed to be consisted of the channel distortions of the whole training data and the current utterance. In this paper, we use a Gaussian distribution to stand for the distribution of additive noise, and adaptive learn the combination factors of the channel distortions. The current method has been proved better than the former one by experiments.