This is the author’s version of a work that was accepted for publication in Computer Speech & Language. Changes resulting from the publishing process, such as peer review, editing, corrections, structural formatting, and other quality control mechanisms may not be reflected in this document. Changes may have been made to this work since it was submitted for publication. A definitive version was subsequently published in Computer Speech & Language, 20, 2-3, (2006) DOI:10.1016/j.csl.2005.08.004 ; The use of quality information for multilevel speaker recognition systems is addressed in this contribution. From a definition of what constitutes a quality measure, two applications are proposed at different phases of the recognition process: scoring and multilevel fusion stages. The traditional likelihood scoring stage is further developed providing guidelines for the practical application of the proposed ideas. Conventional user-independent multilevel support vector machine (SVM) score fusion is also adapted for the inclusion of quality information in the fusion process. In particular, quality measures meeting three different goodness criteria: SNR, F0 deviations and the ITU P.563 objective speech quality assessment are used in the speaker recognition process. Experiments carried out in the Switchboard-I database assess the benefits of the proposed quality-guided recognition approach for both the score computation and score fusion stages.