Linear transforms have been demonstrated to successfully achieve on-line speaker and environmental adaptation for robust recognition. This paper explores the gains in computational speed, speaker adaptation convergence rate and recognition performance obtained through the use of multi-resolution sub-band linear transforms in speech recognition. A useful feature of multi-resolution processing is that significant savings can be attained as regards transform calculation. In this paper we appraise the relative merits of multi-band processing over that of full-band and present evaluation results on the WSJCAM0 continuous speech database.