Voice transformation is the process of transforming the characteristics of speech uttered by a source speaker, such that a listener would believe the speech was uttered by a target speaker. In this paper we address the problem of transforming voice quality. We do not attempt to transform prosody. Our system has two main parts corresponding to the two components of the source-filter model of speech production. The first component transforms the spectral envelope as represented by a linear prediction model. The transformation is achieved using a Gaussian mixture model, which is trained on aligned speech from source and target speakers. The second part of the system predicts the spectral detail from the transformed linear prediction coefficients. A novel approach is proposed, which is based on a classifier and residual codebooks. On the basis of a number of performance metrics it outperforms existing systems.