This paper describes the use of denoising techniques in the time domain applied to the outputs of filters corresponding to a Multi Resolution Analysis. The fact that energies of denoised samples are used for Automatic Speech Recognition (ASR) makes soft thresholding particularly attractive especially if Principal Component Analysis (PCA) is applied to the whole tree of energy features. This consideration is supported by experimental results on a very large test set including many speakers uttering proper names from different locations of the Italian public telephone network. The results show that soft thresholding outperforms J-Rasta PLP with a WER reduction, after denoising, of 26%.