1. A system for applying feature-space maximum likelihood linear regression (fMLLR) to correlated features, the system comprising: at least one memory and at least one processor operatively coupled to the at least one memory; a semi-tied covariance (STC) module executed via the at least one processor, and capable of mapping the correlated features into an uncorrelated feature space; an fMLLR module executed via the at least one processor, and capable of applying fMLLR in the uncorrelated feature space to obtain fMLLR transformed features; and a return module executed via the at least one processor, and capable of mapping the fMLLR transformed features back to a correlated feature space; wherein the system obtains the correlated features by: receiving an input signal; computing a transform of the input signal; and applying a filter bank to the transformed input signal.